Biomarkers of lung function

ABSTRACT

Cigarette smoking is a primary determinant of chronic obstructive pulmonary disease (COPD), which is the fourth leading cause of morbidity and mortality in the United States. Unique proteins associated with COPD capable of differentiating subjects likely to experience rapid (RPD) or slow (SLW) decline in lung function have been identified using comprehensive high-throughput proteomic approaches. Thirty peptides, which mapped to 21 unique proteins, were linearly associated with annualized rates of lung function decline among smokers with COPD characterized as having rapid or slow decline and smokers without COPD. Using three different statistical approaches to assess the data, the RPD and SLW groups are differentiated by 55 peptides, which mapped to 33 unique proteins. A number of the identified peptides are proteolytic fragments of proteins that are involved in the complement and/or coagulation systems, have anti-protease activity, or metabolic functions.

This application is a continuation of International Application No.PCT/US2011/020151, filed Jan. 4, 2011, which claims the benefit of U.S.Provisional Application No. 61/292,151, filed Jan. 4, 2010, both ofwhich are entitled: “BIOMARKERS OF LUNG FUNCTION”, each of whichapplication is herein incorporated by reference in its entirety.

BACKGROUND

Lung disease, including airway diseases that affect lung function,includes asthma, obstructive pulmonary disease, emphysema, pneumonia,tuberculosis, lung cancer, pulmonary fibrosis, sarcoidosis,HIV/AIDS-related lung disease, alpha-1 antitrypsin deficiency,respiratory distress syndrome, bronchopulmonary dysplasia, embolism, andchronic obstructive pulmonary disease (COPD), among others.

COPD is the fourth leading cause of morbidity and mortality in theUnited States and is expected to rank third as the cause of deathworldwide by 2020 (1). Cigarette smoking is widely recognized as aprimary causative factor of COPD and accounts for approximately 80-90%of all cases in the United States (2). It has been estimated that up to25-50% of cigarette smokers may develop CORD, and its prevalenceincreases with age (1-4).

The pulmonary component of CORD is primarily characterized by chronicairway inflammation and incompletely reversible, usually progressive,airflow obstruction (5, 1). The operational diagnosis of CORD hastraditionally been made by spirometry, as a ratio of the forcedexpiratory volume in one second (FEV₁) to the forced vital capacity(FVC) below 70% (1). Pathophysiological mechanisms believed to underlieCORD include an imbalance between proteinase and anti-proteinaseactivity in the lung, dysregulation of anti-oxidant activity and chronicabnormal inflammatory response to long-term exposure to noxious gases orparticles leading to the destruction of the lung alveoli and connectivetissue (5, 1). However, CORD is increasingly recognized as a syndromeassociated with significant systemic effects which are attributed tolow-grade, chronic systemic inflammation (6, 7, 8, 9).

Conventional methods of diagnosing lung disease such as COPD employdiagnostic tests which rely on the presumed correlation of decreasedpulmonary function with the presence of lung disease such as COPD,asthma, fibrosis, emphysema and others. Spirometry, which is the mostcommonly performed lung function test measures the quantity of air thata subject can exhale and the speed with which the air is exhaled. Whilelung function tests can provide a general assessment of the functionalstatus of a subject's lungs, they do not distinguish between thedifferent types of lung diseases that may be present. Certain lungrelated diseases cannot be confirmed based on functional tests alone. Inaddition, such tests assist in the diagnosis of lung disease only whenan abnormality in lung function already exists. Functional diagnosticmethods at a single time point also do not predict the rate ofprogression of the disease.

In contrast to functional diagnostic methods, assessment ofprotein/peptide biomarkers can be used as diagnostic as well asprognostic indicators of the progression (e.g., predicted rate ofprogression) of a disease. Thus, the identification of proteins, such asthose found in plasma, whose abundance and/or structure is altered inindividuals with lung disease can be used to diagnose the presence ofdisease, provide a prognosis for an individual with lung disease (i.e.,predicted rate of progression), and provides a better understanding ofbiological mechanisms underlying a disease.

SUMMARY

Although cigarette smoking is recognized as the most importantenvironmental cause of COPD, the pathophysiological mechanismsunderlying cigarette smoking-related lung function decline are not wellunderstood. The present disclosure provides information regarding themechanisms involved in CORD, particularly cigarette smoking-relatedCOPD, by identifying a number of plasma peptides and proteins and genesencoding plasma proteins that correlate with lung function or decline inlung function. The present disclosure also describes the use of thosepeptides and proteins or genes encoding such proteins as biomarkers oflung function decline. The present disclosure also provides informationregarding the mechanisms underlying lung function or the rate of lungfunction decline among subjects with COPD, including adult cigarettesmokers with COPD. The plasma peptides and proteins have been identifiedby the utilization of robust plasma proteomic techniques, statisticalanalysis and biological pathway analysis. The peptides, proteins andgenes encoding such proteins may be used as biomarkers in the diagnosisand prognosis of diseases including lung diseases such as COPD.

The plasma peptides and proteins provided in this disclosure wereidentified by two proteomic investigations (described herein below asExample 1 and Example 2). The first proteomic investigation discussed inthis disclosure used offline strong cation exchange (SCX) fractionationof samples with reverse phase liquid chromatography coupled to a massspectrometer fitted with electrospray ionization (RP-LC-ESI-MS).Following robust statistical analysis (using two approaches) anddatabase searching, 1,758 peptides were identified in plasma samplesfrom cigarette smokers. Thirty of those peptides mapped to 21 uniqueproteins and were linearly associated with annualized rates of lungfunction decline over 5 years among smokers with COPD who werecharacterized as having rapid or slow (or absent) decline and smokerswithout COPD. A number of the identified peptides are proteolyticfragments of proteins that are involved in the complement or coagulationsystems or which have anti-protease or metabolic functions.

The second proteomic investigation involved the examination of theplasma proteomes of middle-aged or older adult smokers with mild tomoderate COPD, with FEV₁ decline characterized as either rapid or slow(or absent), using a comprehensive high-throughput proteomic approach,and accurate mass and time (AMT) tag technology. Proteomic data wereanalyzed using three statistical approaches that permitted the rapid andslow decline groups to be differentiated by 55 peptides that map to 33unique proteins. Twelve of the proteins have known roles in thecomplement or coagulation cascade and suggest potential mechanisticbiomarkers associated with the rate of lung function decline in COPD.

The present disclosure provides in one aspect a method of diagnosing thepresence of, or predicting the rate of lung function decline in asubject with lung disease, comprising determining the level of one ormore proteins in Table 7, Table 2 or Table 4, or one or more peptidefragments of one or more proteins in Table 7, Table 2 or Table 4, in abiological sample from said subject. In one embodiment, a determinationof the level of one or more proteins in Table 7, Table 2 or Table 4, orone or more peptide fragments of one or more proteins in Table 7, Table2 or Table 4, are used as an indicator of the presence of lung diseasein an individual subject and/or its rate of progression. Determinationsof the levels of one or more proteins in Table 7, Table 2 or Table 4, orone or more peptide fragments of one or more proteins in Table 7, Table2 or Table 4, may also be used to assign individuals to one or moresubpopulations (e.g., subpopulations of individuals having a higher riskfor COPD with rapid progression or slower progression of lung functiondecline). In another embodiment, the level of expression of one or moregenes encoding one or more proteins in Table 7, Table 2 and/or Table 4may be determined (e.g., by reverse transcription-polymerase chainreaction or real time PCR) in place of determining the level of proteinor peptides translated from the gene products.

Determinations of proteins, peptides, or genes may be made relative to asample from an individual or a population of individuals not having lungdisease, or relative to an added external standard or internal standardsuch as a different protein.

The present disclosure provides in another aspect a method of diagnosisof or prognosis for a subject having, or suspected of having, a disease(e.g., lung disease such as COPD), comprising determining the level ofone or more proteins in Table 2 or Table 4, or one or more peptidefragments of one or more proteins in Table 2 or Table 4, in a biologicalsample from said subject. In one embodiment the disease is selected fromthe group consisting of, but not limited to, obstructive pulmonarydisease, chronic systemic inflammation, emphysema, asthma, pulmonaryfibrosis, cystic fibrosis, obstructive lung disease, COPD, and pulmonaryinflammatory disorder. In one embodiment, the disease is COPD.

The methods of providing a diagnosis or prognosis provided herein mayadvantageously employ samples of biological fluids from a variety ofsources, including, but not limited to blood, plasma, serum, lymphaticfluid, sputum, saliva, and/or urine for the direct determination oflevels of proteins or peptides, or the indirect determination of levelsof proteins or peptides through a measurement of the levels of nucleicacids encoding them. In one embodiment the biological fluid is plasma.

The methods of providing a diagnosis or prognosis provided herein mayadvantageously employ analytical methods of determining protein orpeptide levels in biological fluids including, but not limited to,liquid chromatography separation with mass spectroscopic analysis(LC-MS) where the MS techniques include, but are not limited to,multistage mass spectrometric analysis, data dependent scanning, production scans, single ion monitoring, single reaction monitoring, andmultiple reaction monitoring. Other methods/techniques of determiningthe level of proteins/peptides present in samples may also be used suchas, for example, immunological detection and immunoaffinity techniques(e.g., ELISA, Western blotting, and various forms of immunologicalsandwich assays).

Also provided herein are compositions comprising two, three, four, five,six, seven or more proteins or peptide fragments that may be employed inmethods of providing a diagnosis or prognosis of a subject having, orsuspected of having, a disease (e.g., lung disease such as COPD). In oneembodiment, the compositions may comprise proteins or fragments ofproteins identified in Table 2, Table 4, or combinations thereof.

In other embodiments, the present disclosure provides compositionscomprising two, three, four, five, six, seven or more nucleic acidsencoding the proteins and/or peptides identified in Table 2 or Table 4,and optionally comprising at least one promoter operatively coupled toat least one of said nucleic acids. In one embodiment such compositionmay comprise one, two, three, four, five, six, or more oligonucleotideshaving at least 80-90 percent, 80-95 percent, 85-95 percent, or 95-100percent nucleic acid sequence identity to a contiguous sequence of 21 ormore nucleotides of a nucleic acid sequence encoding the proteinsidentified in any of Tables 7, 2 or 4 or fragments thereof.

Also provided are a compositions comprising one or more, two or more,three or more, four or more, five or more, or ten or more differentantibodies or fragments thereof, wherein said different antibodies, orantigen binding fragments thereof, are specific to two or more differentproteins or peptide fragments identified in any of Table 7, Table 2 orTable 4. In some embodiments, the compositions comprise three, four,five, six seven or more different antibodies, or antigen bindingfragments thereof, each specific for a different protein or peptidefragment identified in Table 2 or Table 4.

In another embodiment, the compositions described herein are in the formof: an array having two or more proteins or peptide fragments covalentlyattached to two or more different spatially addressable locations; anarray having two or more antibodies or antigen binding fragments thereofcovalently attached to two or more different spatially addressablelocations; or an array having two or more nucleic acids covalentlyattached to two or more spatially addressable locations.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram prepared using Pathway Studio™ software by AriadneGenomics, showing nine proteins having multiple relationships (asdetermined via natural language processing of published abstractsaccessible in pubmed.gov) to 21 of the proteins identified asdifferentially expressed across the three groups of subjects describedin Example 1. The nine proteins identified by Ariadne Genomics' PathwayStudio™ are Insulin 2 (proinsulin) (INS), Plasminogen (PLG), Fibrinogen,alpha polypeptide (FGA), Interleukin 6 (IL6), Coagulation factor II(F2), Interleukin 1 beta (IL1B), Signal transducer and activator oftranscription 3 (STAT3), Cyclin dependent kinase 2 (CDK2), and FAM3A(family with sequence similarity 3, member A). Those nine proteins areshown in relation to other proteins identified as differentiallyexpressed.

FIG. 2 is a Venn diagram representing an overlap of the peptides (lowernumber in each pair in italics) and associated non-redundant proteins(upper number in each set not italicized) identified using the threedifferent statistical methods described in Example 2.

FIG. 3 is a representation of those proteins identified in Example 2that are known to be part of the coagulation or complement cascade, andtheir association with other proteins/peptides.

DETAILED DESCRIPTION

The present disclosure describes methods of analyzing the protein,peptide, and/or polypeptide content of biosamples to aid in theunderstanding of molecular mechanisms involved in the development,progression, and/or prognosis of diseases (e.g., lung disease such asCOPD) in a subject. Methods are provided for using the abundance ofproteins and peptides as biomarkers for diagnostic, prognostic and/orpredictive measures of a subject's disease, management of the subject'sdisease, and/or prediction of the subject's response to clinicaltreatments for the lung disease. In one embodiment, the disease includescigarette smoking-related COPD which is assessed by identifying plasmaproteins that are differentially expressed and correlate with differentrates of decline in lung function (FEV₁). Measurements of the abundanceof expressed nucleic acids encoding proteins, peptides, and polypeptidesmay also be used as surrogates for the measurement of these proteins,peptides and polypeptides in the methods described herein.

In addition to providing information such as the name of the protein andthe name of the gene encoding the proteins identified herein, the NCBIaccession number and version and/or the GI number (aka “gi number”) isprovided for each protein. The NCBI accession/version numbers and GInumbers uniquely identify nucleic acid and/or protein sequences presentin the NCBI database (NCBI, U.S. National Library of Medicine, 800Rockville Pike, Bethesda, Md., 20894 USA), and are publicly available,for example, on the word wide web at www.ncbi.nlm.nih.gov. Where an NCBIaccession number is provided for a precursor protein it is understoodthat the corresponding mature protein is also available in the NCBIdatabase and considered part of this disclosure unless expressly statedotherwise. In addition, recitation of the protein sequences providedherein indicates that the corresponding gene sequence(s) encoding eachprotein are also available in the NCBI database at the time of thisdisclosure and its priority document. Where any accession number doesnot recite a specific version, the version is taken to be the mostrecent version of the sequence associated with that accession number atthe time the earliest priority document for the present application wasfiled.

For each proteins recited herein it is understood that the NCBIaccession numbers and GI numbers only refer to a sequence that isexemplary of the proteins (and their peptides) encompassed by thisdisclosure. Unless recited otherwise, the present disclosure includesall isoforms of the proteins identified herein. Isoforms include, butare not limited to: proteins encoded by alternate alleles and haplotypesof the same gene; and/or proteins produced by alternate splicing oftranscripts from one or more alleles of the same gene or other forms ofalternative processing, including changes due to epigenetic influences.In some embodiments, isoforms include proteins/polypeptides that sharegreater than 70, 80, 85, 90, 95, 97, 98, or 99% sequence identity overthe length of the shorter of the two proteins/polypeptides. In oneembodiment, the isoforms of proteins share the amino acid sequence ofthe peptides recited for the proteins listed in Tables 2, 4 and 7.

In one embodiment an individual or a population of individuals may beconsidered as not having lung disease or impaired lung function whenthey do not have clinically relevant signs, symptoms, and/or measures oflung disease. Thus, in various aspects, an individual or a population ofindividuals may be considered as not having chronic obstructivepulmonary disease, chronic systemic inflammation, emphysema, asthma,pulmonary fibrosis, cystic fibrosis, obstructive lung disease, pulmonaryinflammatory disorder, or lung cancer when they do not manifestclinically relevant signs, symptoms and/or measures of those disorders.In another embodiment, an individual or a population of individuals maybe considered as not having lung disease or impaired lung function, suchas COPD, when they have a FEV₁/FVC ratio greater than or equal to about0.70 or 0.72 or 0.75. In another embodiment, an individual or populationof individuals that may be considered as not having lung disease orimpaired lung function are sex- and age-matched with test subjects(e.g., age matched to 5 or 10 year bands) that are current or formercigarette smokers without apparent lung disease who have anFEV₁/FVC≥0.70 or ≥0.75. Individuals or populations of individualswithout lung disease or impaired lung function may be employed toestablish the normal range of proteins, peptides or gene expression.Individuals or populations of individuals without lung disease orimpaired lung function may also provide samples against which to compareone or more samples taken from a test subject (e.g., samples taken atone or more different first and second times) whose lung disease or lungfunction status may be unknown. In other embodiments, an individual or apopulation of individuals may be considered as having lung disease orimpaired lung function when they do not meet the criteria of one or moreof the above mentioned embodiments.

Identification of Protein(s) and/or Peptide(s) Associated with COPD orits Progression at a Slow or Rapid Rate.

The present disclosure provides in one embodiment a method foridentifying protein or peptide biomarkers of a disease that areassociated with either the presence of a lung disease, or a slow or arapid decline in lung function, as measured by a decline in FEV₁, insubjects with a lung disease. In one embodiment the lung disease isCOPD, which affects the lungs and also the tissues of other organs.

In one embodiment, proteins and/or peptides are identified usingexpression profiling of samples of a tissue, cells or fluids (e.g.,biofluids such as serum, plasma, urine, sputum, saliva, lymph, and thelike) from subjects with a lung disease as compared to a profile ofpeptides in subjects without the disease. In another embodiment, thepresent disclosure provides polypeptide-based biomarkers that aredifferentially present in subjects with lung disease versus individualswithout lung disease.

In another embodiment, a method for identifying protein and/or peptidebiomarkers of a disease that is associated with a decrease in lungfunction comprises:

-   -   a) obtaining an expression profile of proteins and/or peptides        in a biological sample from at least one subject (case sample)        diagnosed as having a preselected disease that is associated        with a decline in lung function (case);    -   b) obtaining an expression profile of proteins and/or peptides        in a biological control sample from at least one subject        identified as not having the disease (control);    -   c) identifying one or more proteins and/or peptides that are        differentially expressed in the sample from the subject (case        sample) as compared to the control sample; and    -   d) optionally performing a statistical analysis on abundance        values of the one or more identified proteins and/or peptides,        wherein a statistically significant difference in abundance of        the identified peptide(s) and/or protein(s) in the case sample        as compared to the control sample identifies the peptide or        protein as a biomarker of the preselected disease.

The profiling of proteins and/or peptides may be conducted by any methodknown in the art including, but not limited to, various massspectroscopic methods. In some embodiments, proteins/peptides profilesare obtained by liquid chromatography separation of a sample coupled tomass spectroscopic analysis (LC-MS), where the mass spectroscopicanalysis techniques including, but are not limited to, multistage massspectrometric analysis, data dependent scanning, product ion scans,single ion monitoring, single reaction monitoring, and multiple reactionmonitoring. Other techniques/instrumentation that may be employed forthe analysis of proteins and peptides, include, but are not limited to,FT-ICR MS, LC FT-ICR MS, accurate mass and time (AMT) technology,putative mass and time (PMT) technology, high resolution LC separationsand high mass accuracy measurements, MALDI, ESI, offline SCXfractionation with RP-LC-ESI-MS/MS, two-dimensional gel electrophoresis,immunoaffinity methods (e.g., ELISA, Western blotting, in situimmunohistochemistry) and protein array analysis.

In another embodiment, the present disclosure provides a method of usingone, two, three, four, five, six seven, eight, ten, fifteen or moredifferent proteins and/or peptides for diagnosing the presence of a lungdisease or for developing a prognosis of the rate of lung functiondecline in a subject.

In another embodiment, the present disclosure provides a method of usingone, two, three, four, five, six seven, eight, ten, fifteen or moredifferent proteins and/or peptides for evaluating lung function in thepresence of a lung disease or in the absence of a lung disease, or fordeveloping a prognosis of lung function in a subject.

In one aspect, this disclosure also provides methods for comparison ofdifferential protein/peptide expression in one or more subjects withlung disease relative to one or more individuals without lung disease,or in subjects having lung disease such as COPD with little or nodecline in lung function, such as by measurement of FEV₁, compared withsubjects having lung disease such as COPD with rapid decline in lungfunction. In one embodiment such methods comprise determining the levelof one or more proteins that are set forth in Tables 2 and/or 4, orpeptide fragments of those proteins or the level of expression of genesencoding those proteins.

This disclosure also provides methods for comparing differential proteinexpression in subjects with lung disease. Such individuals may bedivided into groups having rapid or slow rates of decline in lungfunction by determining the annualized rate of lung function decline fora subject as the slope of the linear regression of FEV₁% predicted(i.e., adjusted for age, sex, and height). Subjects with the steepestrate of decline in annualized FEV₁% predicted (greater than the averageannual decline) are considered to have COPD with “rapid decline” (RPD).Those individuals with the least steep or no annualized rate of declinein FEV₁% predicted (less than the average) are considered to have COPDwith slow decline (SLW).

In one embodiment proteins present in a biological sample obtained fromone or more cigarette smokers having COPD with rapid decline in lungfunction may be compared to proteins present in biological samplesobtained from cigarette smokers having COPD with slow decline in lungfunction (SLW), or may be compared to proteins present in biologicalsamples obtained from smokers without COPD or from non-smokers, toidentify proteins or peptides differentially expressed in those groups.

Comparison of the differentially expressed proteins identifies potentialprotein/peptide biomarkers useful for classifying the lung condition ordisease (e.g., as slow- or rapid-decline COPD) presented by a subject.Protein/peptide biomarkers may also be identified by analysis ofproteins differentially expressed by a subject with a lung disease ascompared to proteins expressed by a gender-matched subject without lungdisease. Identification of proteins that are differentially abundantamong different groups of subjects with lung disease (e.g., age andgender matched subjects) allows an understanding of the mechanisms(e.g., molecular changes) underlying a lung disease and the relateddecline in lung function. Such proteins are useful as molecularbiomarker(s) for diagnosis, determining prognosis, and/or management ofa subject's lung disease. For example, the proteins/peptides providedherein can be used for diagnosis and/or prognosis of rate of lungfunction decline in a subject with a lung disease.

In one embodiment, protein expression among one or more groups of adultcigarette smokers with mild to moderate COPD, but different rates oflung function decline, such as rapid- or slow-decline, may be comparedto gender-matched smokers without COPD. Identification of proteins thatare differentially abundant among the groups reflects the mechanismsunderlying cigarette smoking-related lung function decline. Suchproteins/peptides are molecular biomarkers for COPD and are useful indiagnosis, prognosis and/or management of COPD.

In another embodiment a method for identifying protein and/or peptidebiomarkers of a disease that is associated with a rapid or slow decrease(decline) in lung function comprises:

-   -   a) obtaining an expression profile of proteins and/or peptides        in a biological sample from at least one subject diagnosed as        having a preselected disease that is associated with a decline        in lung function (case);    -   b) obtaining an expression profile of proteins and/or peptides        in a biological control sample from at least one subject        identified as not having the disease (control);    -   c) identifying one or more proteins and/or peptides that are        differentially expressed in the case sample as compared to the        control sample; and    -   d) optionally performing a statistical analysis on abundance        values of the one or more identified proteins and/or peptides,        wherein a statistically significant difference in abundance of        the identified peptide(s) and/or protein(s) in the case sample        as compared to the control sample identifies the peptide or        protein as a biomarker of the preselected disease.

For the purpose of this disclosure, the term “peptides” includespeptides prepared synthetically, or by any form of proteolysisincluding, but not limited to, enzymatic proteolysis. Such peptides maybe limited to those peptides with a length greater than seven, eight,nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen,seventeen, eighteen, twenty, twenty two, twenty five, thirty, or thirtyfive amino acids. Such peptides may also be less than 40, 50, 60, 70,80, or 100 amino acids in length. Alternatively, such peptides may havea range from about 7 to 50, 9-25, 10 to 20, 8 to 24, 9 to 18, 12 to 24,15 to 45, 18 to 40, 20 to 50, or 25 to 50 amino acids in length.

Methods of Providing a Diagnosis or Prognosis of a Subject Having, orSuspected of Having, a Lung Disease Including COPD

Methods are provided for the diagnosis or prognosis of a subject having,or suspected of having, a lung disease, comprising making adetermination of one or more proteins in Table 7, or one or morepeptides of a protein in Table 7, in a biological sample from a subject.Optionally, the methods comprise making a determination of one or moreproteins in Tables 2, 4, 5 and/or 6, or one or more peptides of one ormore proteins in Tables 2, 4, 5 and/or 6. In such methods two or more,three or more, four or more, five or more, six or more, eight or more,ten or more, fifteen or more, twenty or more, twenty five or more,thirty or more, or forty or more different proteins or peptides fromdifferent proteins in Tables 2, 4, 5 6 and/or 7 may be determined.

Methods are provided for the diagnosis or prognosis of a subject having,or suspected of having a lung disease, comprising determining the levelof one or more proteins in Table 7 and/or in Table 2 or Table 4 or oneor more peptide fragments of one or more proteins in Table 7 and/or inTable 2 or Table 4, in a biological sample from said subject. In someembodiments the disease is selected from the group consisting of but notlimited to obstructive pulmonary disease, chronic systemic inflammation,emphysema, asthma, pulmonary fibrosis, cystic fibrosis, obstructive lungdisease, COPD, and pulmonary inflammatory disorder.

Assessment of the level of one or more proteins found in Tables 2 and/or4, or fragments thereof, provides information for diagnosing lungdiseases such as COPD, or for providing a prognosis of lung disease(e.g., COPD progression).

In one embodiment, a method of determining a prognosis of a lung diseasecan include determining the abundance (quantity or concentration) of oneor more biomarkers present in a biological sample obtained from asubject, wherein the one or more biomarkers are selected from the groupconsisting of: a blood coagulation pathway component (protein), acomponent of the renin-angiotensin pathway, a complement system protein,a growth factor, a cytokine, a binding protein, a plasma glycoprotein,an anti-inflammatory protein, an immunoglobulin, and a lipoprotein. Inanother embodiment, a method of determining prognosis of a lung diseasecan include determining the quantity or concentration of one, two,three, four, five, six, seven, eight, nine, ten, twelve, fifteen, ormore proteins listed in Table 7 and/or in Table 2 or Table 4 (orpeptides of such proteins) or of transcripts from genes coding for theproteins listed in Table 7 and/or in Table 2 and 4.

In another embodiment, the present disclosure provides a method ofmanaging a subject's lung disease, wherein a therapeutic treatment planis customized or adjusted based on the status of the disease asdetermined by assessment of one or more proteins and/or peptidefragments of such proteins identified in Table 7, and/or Tables 2 and/or4. Exemplary therapeutic treatments for lung disease includeadministering to the subject, one or more of: immunosuppressants,corticosteroids (e.g. betamethasone delivered by inhaler), b2-adrenergicreceptor agonists (e.g., short acting agonists such as albuterol),anticholinergics (e.g., ipratropium, or a salt thereof delivered bynebuliser), and/or oxygen. In addition, where the lung disease is causedby or exacerbated by bacterial or viral infections, one or moreantibiotics or antiviral agents may also be administered to the subject.In other embodiments a method of treatment comprises measuring at leastone protein or peptide fragment of a protein identified in Table 7,and/or in Tables 2 and/or Table 4, during the course of the subject'slung disease. In such an embodiment, the level of expression of aprotein in Table 7, and/or in Table 2 and/or Table 4, may also beassessed by measurement of the nucleic acids (mRNAs) expressed from thegene encoding the protein as surrogate for measuring the proteindirectly. The course of lung disease may be determined by making a firstdetermination (e.g., taking a first measurement) at a first time, of atleast one protein or peptide fragment of a protein identified in Table7, and/or in Tables 2 and/or Table 4, or mRNA encoding a protein aprotein identified in Table 7, and/or in Tables 2 and/or Table 4, in afirst sample from the subject; and making a second determination of atleast the same protein, peptide fragment or mRNA in a second biologicalsample obtained from the subject at a second time; and comparing thefirst determination to the second determination to determine the lungdisease is in progression or regression. A method of managing asubject's treatment includes selecting an initial treatment protocol oraltering a preselected treatment protocol based on the status or changein the status of the lung disease from the measurements at the first andsecond times. In other aspects, the method further comprises measuringtwo, three, four, five, six, seven, eight, ten, twelve, fifteen or moredifferent proteins or peptide fragments of proteins listed in Tables 2and/or 4, or the level of gene expression (e.g., mRNA levels) for thoseproteins at one or more times during the management of a subject's lungdisease. Any one or more of the proteins identified in Table 5 and/orTable 6, or peptide fragments thereof, may also be employed in suchmethods of treatment, following the course of lung disease, or managinga subject's treatment.

In another embodiment, the present disclosure provides a method formonitoring the course of progression of a lung disease in a subjectcomprising: (a) obtaining a first measurement of at least one protein orpeptide fragment of a protein listed in Table 7, and/or Table 2 and/orTable 4, or the level of gene expression (e.g., mRNA levels) for thatprotein in a first biological sample from the subject; (b) obtaining asecond measurement of at least the same one protein, peptide fragment orlevel of gene expression in a second biological sample from the subject,where the second biological sample is obtained from the subject afterthe first biological sample; and (c) correlating the changes in thefirst and second measurements with a progression, lack of progression,or regression of lung disease in the subject. Any one or more of theproteins identified in Table 5 and/or Table 6, or peptide fragmentsthereof, may also be employed in such methods.

Where determinations of one or more proteins or peptide fragmentsindicate that a treatment administered to a subject is ineffective, thedeterminations may be taken to indicate that higher levels of an appliedtherapeutic may be required to effect treatment, the protocol foradministration may need to be modified, or that a different therapeuticagent is required. Where determinations of one or more proteins indicatethat a treatment administered to a subject is effective, thedeterminations may be taken to indicate that the course of therapy(e.g., the choice or dosage of therapeutic agent(s) and/or the protocolfor administration) should be continued. Where a treatment is onlymarginally effective based upon the determinations, either a change inthe treatment, or an increase in the dosage of a therapeutic agentalready being administered to the subject may be indicated.

In embodiments where changes in the levels of the proteins identified inTables 2, 4 or 7 are observed over time, an increase in at least oneprotein identified in any of Tables 2, 4 or 7 that is associated withprogression of COPD at a slow or rapid rate is indicative of diseaseprogression. In contrast the decrease in at least one protein identifiedin any of Tables 2, 4 or 7 may be indicative of a lack of diseaseprogression or may be indicative of disease regression. Similarly, anincrease in a protein identified in any of Tables 2, 4 or 7 associatedwith stable COPD is indicative of stability or regression of thedisease. Determinations of proteins (e.g., changes in level or amount)may be made by obtaining measurements of the intact protein, peptidefragment(s) of the protein, or nucleic acids (e.g. mRNA) encoding theprotein in samples (e.g., first and second samples) obtained from thesubject at different times.

Samples for the Identification and Determination of Protein/PeptideProfiles or the Levels of Proteins and/or Peptides

Biological sources for detection and determination of the levels ofprotein/peptide biomarker(s) include any tissue of interest from asubject suspected of having, or diagnosed as having, a disease (e.g., alung disease such as COPD). In one embodiment, samples for detection ofprotein(s) and/or peptide(s) of interest include, but are not limitedto, serum, plasma, blood, lymphatic fluid, cerebral spinal fluid, sputumor saliva. In another embodiment a protein/peptide biomarker may bedetected and levels determined in plasma.

Determination of Protein and Peptide Abundance Levels in Samples

Protein and peptide biomarkers provided herein that are correlated withdiseases such as COPD or its progression may be identified without priorknowledge of their identity. For example, a biomarker's amino acidsequence can be determined using peptides present in a sample, peptidesfrom enzymatic digests of a protein containing sample, or peptidesderived by sequencing (e.g., sequencing using mass spectroscopy). Asequence for a peptide can be compared to a database of known proteinsto identify the proteins from which the peptide was derived.

For the purpose of this disclosure “determination”, “determine”, or“determining” means measuring or observing the quantity (e.g., mass,weight, or number of moles) of a material or substance or theconcentration of a material or substance. Determinations may be made ofrelative amounts of a material or substance (e.g., the amount of proteinin a sample is twice that of the control sample) without ascertaining anabsolute amount, provided the determination permits any relevantcomparison to be made or method recited herein to be conducted.

Proteins and peptides differentially expressed in subjects having lungdiseases such as COPD or in patients with different rates of decline inlung function may be identified and/or their levels measured using avariety of techniques that may be applied to sample protein and/orproteomic analysis. Exemplary methodologies include, but are not limitedto, the use of chromatographic separation techniques such as2-dimensional (2-D) gel electrophoresis, intact protein fractionation,peptide fractionation, and nano-flow liquid chromatography (LC).Analysis of peptides in proteomic studies may employ mass spectrometry(MS), which is a detection technique often used in either matrixassisted laser desorption ionization (MALDI) or electrospray ionization(ESI) for peptide analysis. The MS platforms by which measurements aremade include instruments configured as quadrupole, time-of-flight (TOF),ion-trap, and Fourier transform ion cyclotron resonance MS (FTMS)instruments, or hybrid instruments such as triple quadrupole,quadrupole-TOF and ion-trap-FTMS. Recent observations by the HumanProteome Organization's (HUPO) Plasma Proteome Project have shown thatoffline peptide separation by strong cation exchange (SXC) followed byreverse-phase (RP) LC with ESI-MS/MS can result in the identification ofmore proteins of low abundance. See Li, et al., 2005 (10), which ishereby incorporated by reference in its entirety. Methods that combineimmunological capture and of peptides coupled with mass spectroscopicanalysis may also be employed in the methods described herein. See,e.g., U.S. Pat. No. 7,632,686 and U.S. Pat. No. 6,872,575 each of whichare incorporated by reference herein.

In one embodiment, determination of a protein and/or peptide present ina biological sample can include its capture on a chromatographic resinthat binds the protein and/or peptide. For example, a protein and/orpeptide may be captured using a strong or weak cation exchange resinfollowed by elution. The eluted protein and/or peptide can then bedetected by a mass spectrometry method. In another alternative, aprotein and/or peptide can be fractionated on an anion exchange resinand detected directly by a mass spectrometry method. In yet anothermethod, a protein and/or peptide can be captured on animmuno-chromatographic resin comprising antibodies that bind the proteinand/or peptide followed by a specific detection method or a detectionmethod allowing determination of a protein or peptide level oridentification of the protein and/or peptide, such as ELISA or a massspectrometry method.

Other methods/techniques of isolating, identifying and determining thelevel of proteins/peptides present in samples include, but are notlimited to, SDS-PAGE electrophoresis, two-dimensional gelelectrophoresis, intact chromatographic protein fractionation, andpeptide chromatographic fractionation, quantitative ligand-binding, andnano-flow liquid chromatography (nano-flow LC).

Nucleic acids encoding proteins and/or peptides may also be measured assurrogates for measurement of the proteins or peptides themselves (e.g.,gene expression). In such circumstances a variety of techniques may beemployed, including, but not limited to, polymerase chain reaction,nucleic acid array analysis, quantitative RT-PCR (reverse transcriptasePCR), quantitative real time PCR, multiplex PCR, quantitative DNAarrays, quantitative hybridization, chromatography, quantitativerRNA-based amplification, fluorescent probe hybridization, fluorescentnucleic acid sequence specific amplification, loop-mediated isothermalamplification and/or ligase amplification (e.g., ligase chain reaction).

Immunoassays may also be used to identify proteins/peptides thatcorrelate with disease function or for forming a diagnosis or prognosisbased on the levels of proteins or peptides present. Such immunoassaysinclude, but are not limited to, ELISA, immunohistochemistry,immunoelectrophoresis, analysis using arrays of immobilized antibodies,and Western blot analysis.

For the purpose of this disclosure antibodies are intended to includeall type of antibodies, suitable for use in any given procedure unlessspecified otherwise. Antibodies include, without limitation, monoclonalantibodies, (monospecific) polyclonal antibodies, Fab(s), Fab′(s),single chain antibodies, diabodies, domain antibodies, miniantibodies,or an antigen binding fragments of any of the foregoing.

In one embodiment, a biological sample may be analyzed by use of anarray technology and methods employing arrays such as, for example, aprotein or nucleic acid microarray or a biochip bearing an array ofproteins (e.g., antibodies) or nucleic acids. A protein array or biochipgenerally comprises a solid substrate having a generally planar surface,to which a capture reagent is attached. Frequently, the surface of anarray or biochip comprises multiple addressable locations, each bearinga bound capture reagent. In one embodiment the arrays permits thedetection and/or determination (quantitation) of two, three, four, five,six seven, eight, ten, fifteen or more different biomarkers associatedwith COPD or its progression at a slow or rapid rate. In anotherembodiment the array comprises addressable locations for analysis oftwo, three, four, five, six seven, eight, ten, fifteen or more differentproteins or peptide fragment(s) of proteins identified in any of Tables2, 4 or 7. In another embodiment the array comprises addressablelocations for analysis of two, three, four, five, six seven, proteins orfragments of proteins from the group consisting of: a blood coagulationpathway, a component of the renin-angiotensin pathway, and a complementsystem protein, identified in any of Tables 2, 4 or 7.

Analysis of proteins and/or peptides described herein may be conductedby detection or measurement of individual proteins and/or peptides or acombination of proteins and/or peptides. For example, methods fordiagnoses, determining prognosis of a lung disease and/or management ofa lung disease in a subject can include use of a composition comprisingat least two proteins and/or peptides described herein. Thus, thisdisclosure includes embodiments or compositions comprising: at least twoproteins and/or peptides; one or more nucleic acid sequence, orfragment(s) thereof, encoding proteins and/or peptides; one or moreoligonucleotides having at least 80 percent identity to a contiguoussequence of at least 9, 12, 15, 18, 21, 24, 27, or 30 nucleotides of anucleic acid sequence encoding a protein and/or peptide; or at least twoantibodies or fragment(s) thereof specific to a protein or peptidedescribed in any of Tables 2, 4 or 7.

The essential materials and reagents required for diagnosing a lungdisease, for determining the prognosis of a lung disease and/or for usein the treatment or management of lung disease in a subject may beassembled together in a kit. The kit generally will comprise componentsand reagents necessary for determining the level of one or more proteinsor peptides (e.g., the proteins or fragments of proteins identified inTables 2 and/or 4) in a biological sample as well as in control and/orstandard samples. For example, a kit may include oligonucleotidesequences, probes, and/or antibodies specific to the one or more of theaforementioned proteins or peptide fragments of those proteins for usein a quantitative assay such as RT-PCR, in situ hybridization, and/ormicroarray assays.

EXAMPLES Example 1: Differential Protein Expression Among Two Groups ofAdult Cigarette Smokers with Mild to Moderate COPD but Different Ratesof Lung Function Decline and a Gender-Matched Group of Smokers withoutCOPD

1.1 Subjects.

Subjects were selected from 244 University of Utah study centerparticipants in the Lung Health Study (LHS) who also participated in thefollow-on Genetics of Addiction Project (GAP). LHS enrolled male andfemale cigarette smokers, aged 35-60 years, with mild or moderate COPD,in a prospective, randomized, multicenter clinical study (11). GAP was across-sectional assessment which also enrolled 94 adult cigarettesmokers without COPD as a control group. Smoking status was assessed andlung function measured by spirometry at baseline (1986-1989), annuallyfor 5 years, once during 1998-2001 (12), and once in GAP (2003-2004).Spirometry included FEV₁ and FEV₁ adjusted for age, sex, and height(i.e., as a percentage of predicted) (1). The annualized rate of lungfunction decline during the 5 years of LHS was calculated for eachparticipant as the slope of the linear regression of FEV₁% predicted.

A subset of 54 GAP participants was selected for plasma proteomicanalysis in this study: the 18 with the steepest rate of decline in FEV₁(rapid decliners, RPD), the 18 with the least steep or no annualizedrate of decline in FEV₁ (slow decliners, SLW), and 18 smokers withoutCOPD as a control group. Characteristics of the three groups are shownin Table 1. Over the first 5 years of LHS, the rapid decliners had anaverage annual decrease in FEV₁ of 1.6% predicted/y while the slowdecliners had an average increase of 0.8% predicted/y. At the GAPassessment approximately 17 years after baseline, 7/18 (39%) of the RPDparticipants and 12/18 (67%) of the SLW participants no longer smokedand in the control group, 8/18 (44%) had quit smoking in the threemonths before GAP participation (χ²=3.11, 2 d.f., p=0.21).

TABLE 1 Characteristics of study participants. Cigarette CigaretteSmokers with COPD, Cigarette Smokers with COPD, Smokers RapidDecline^(a) (RPD) (n = 18) Slow Decline^(a) (SLW) (n = 18) without COPDLung Health Study Lung Health Study (n = 18) Characteristic BaselineYear 5 GAP Baseline Year 5 GAP GAP p-value Male, n (%)  13 (72.2)  10(55.6)    9 (50.0) 0.369^(b) Age, mean (SD) 64.8 (5.4)  63.6 (7.3)  57.2(7.7) 0.002^(c) Cigarettes per Day, 37.3 (17.2) 21.6 (19.0) 16.0 (17.0)27.7 (10.7)  8.3 (11.4) 5.6 (9.5)  9.7 (12.0) 0.167^(c) mean (SD)^(e)Years Smoked, 42.1 (6.8)  34.8 (9.2)   30.1 (11.3) <0.001^(c) mean (SD)FEV₁ (L), mean 2.75 (0.59) 2.34 (0.67) 1.70 (0.60) 2.61 (0.57) 2.63(0.66) 2.32 (0.55)  3.20 (0.63) (SD) Δ FEV₁ (L), mean −0.40 (0.23)  0.02(0.21) na <0.001^(d) (SD) FEV₁ % predicted, 76.1 (9.7)  67.8 (13.3) 54.6(16.6) 74.8 (9.7)  78.5 (12.1) 77.2 (14.2) 103.1 (18.4) mean (SD) Δ FEV₁% −8.22 (7.34)  3.77 (5.73) na <0.001^(d) predicted, mean (SD) GAP,Genetics of Addiction Project, an average of 17 years after Baseline atwhich time plasma proteomic analysis was performed; na, not applicable.^(a)Decline in lung function was assessed as the slope of a linearregression of the annualized rate of decline during the first 5 years ofparticipation in the Lung Health Study in FEV₁ % predicted (i.e.,adjusted for age, height, and gender) ^(b)χ² = 1.99, 2 d.f. test^(c)Test of association between characteristic and lung function at GAPby linear regression ^(d)Change in characteristic from Baseline to Year5 for RPD versus SLW ^(e)At the GAP time point, 7/18 (39%) of RPD, 12/18(67%) of SLW, and 8/18 (44%) of Control subjects had quit smoking; χ² =3.11, 2 d.f., p = 0.21.1.2 Plasma Sampling and Processing.

Plasma was sampled by venipuncture using a sodium citrated Vacutainer®tube at least two hours after eating. Within ten minutes of collection,blood was centrifuged for 15 minutes at 1500 g and 2-6° C. The topmostplasma was removed and further centrifuged at 1500 g for 15 minutes.Plasma samples were shipped on dry ice, stored at −80° C., and thawedjust before analysis.

1.3 Sample Pooling.

In each of the 3 study groups, plasma samples from 6 subjects werepooled to reduce heterogeneity within the group, increase yield oflow-abundance peptides, and minimize instrument run time. Therefore,three pools were evaluated for each of the three study groups, for atotal of nine plasma sample pools. Samples were selected for each poolby applying a random number generator.

1.4 Depletion of High-Abundance Plasma Proteins.

All pooled plasma samples were depleted of the top 12 most abundantproteins using a Beckman Coulter IgY-12 High Capacity spin column (part#A24618) using the recommended manufacturer's procedure. In short, 20 μLof plasma were added to 480 μL of dilution buffer. The samples were thenfiltered through 0.22 μm spin filters by centrifugation for 1 minute at16,000×g. The depletion columns were then centrifuged for 30 seconds at400×g to dry the beads. The end caps were attached and the dilutedplasma samples were added and mixed by inverting the column. The sampleswere placed on a rotator (end to end) and incubated at room temperaturefor 30 minutes. Columns were then inverted and the tips were removed.The samples were then placed in collection tubes and centrifuged for 30seconds at 400×g. and the depleted flow-through was then collected fordigestion.

1.5 Protein Digestion (Plasma)

The depleted flow-through was added to a pre-rinsed Microcon YM-3 (3000Da) molecular weight Cutoff spin cartridge (Millipore), followingmanufacturer's recommended protocol, and centrifuged at 14,000×g until100 μL of retentate remained (˜30 min.). The retentate was thentransferred to a clean microcentrifuge tube and proteins were reducedusing 15 μL of 50 mM ammonium bicarbonate (Pierce) and 1.5 μL of 100 mMDL-1,4-dithiothreitol (Acros, Geel, Belgium) and incubation at 95° C.for 5 minutes. After samples cooled, they were alkylated by the additionof 3 μL of 100 mM iodoacetamide (Pierce) and incubation for 20 minutesin the dark at room temperature. 1.5 μL of 100 ng/μL porcine trypsin(Promega, Madison, Wis.) was then added and the samples were incubatedat 37° C. for three hours. An additional 1.5 μL of 100 ng/μL trypsin wasthen added followed by incubation at 37° C. for approximately 16 hours.To ensure sufficient reagent mixing, all samples were vortexed (30seconds) and centrifuged (2000×g for one minute) following each solutionaddition. Samples were dried in a vacuum centrifuge at 45° C. Sampleswere reconstituted with 50 μL of 3% acetonitrile with 0.1% formic acidand vortexed (30 seconds) prior to fractionation.

1.6 Offline Plasma Fractionation.

Offline fractionation of the plasma tryptic digests in each pooledsample into ten fractions was conducted using a GE healthcare MDLC Ettan(Piscataway, N.J.) fitted with a GE FRAC950 fraction collector fittedwith a strong cation exchange (SCX) column (Thermo Fisher ScientificBiobasic SCX, 250×2.1 mm). Ion exchange (IXE) solvent A was 20 mmol/Lcitric acid (Fisher) in 75% HPLC grade water and 25% acetonitrile(Fisher) (3.8 g citric acid in 1 L of 25% acetonitrile) (pH 2.65). IXEsolvent B was 20 mmol/L citric acid and 1 mol/L ammonium chloride(Fisher) in 75% HPLC grade water and 25% acetonitrile (3.8 g citric acidand 53 g ammonium chloride dissolved in 1 L 25% acetonitrile, pH 2.65).The fraction collector was conditioned for approximately 20 minutesbefore each run with 100% IXE solvent A at 200 μL/minute. The trypticdigest plasma samples were reconstituted in 50 μL of IXE solvent A. Runparameters begin with a 40 μL sample injection and 0% IEX solvent B for10 minutes, ramped to 60% IEX solvent B in 30 minutes, then to 100% IEXsolvent B and held for 5 minutes. The system flow rate was 200 μL/minuteand fractions were collected each minute in a 96 well plate (200 μLfractions). The fractions were lyophilized at 45° C. and stored at −20°C. until analysis. Samples were re-constituted with 50 μL of 3%acetonitrile with 0.1% formic acid and vortexed (30 seconds) prior toanalysis.

1.7 Liquid Chromatography.

All nano-flow capillary liquid chromatography (ncap-LC) analyses wereconducted using an Eksigent nanoLC-1D (Monmouth Junction, N.J.) with aLeap technologies (Carrbaro, N.C.) autosampler and a Zorbax 300SB-C8trap column (5×0.3 mm). Reverse-phase separation was conducted on eachof the ten fractions from each pooled sample using a New ObjectivePicofrit Proteopep™2 (5 cm of C18 packing and a 15 μm tip). The LC runprogram has a 4 minute trap wash at 10 ul/min, a 10 μL injection volumeand a 270 mL/minute flow rate. LC buffer A contains 0.1% formic acid inLCMS grade water (Fisher) and B contains 84% high purity acetonitrile(Fisher) with 0.1% formic acid. The LC gradient starts at 3.5% B andramped to 9% 13 in 1 minute. The gradient was ramped to 70% B in 37minutes, 97% B for 12 minutes and then returned to 3.5% B.

1.8 Mass Spectrometry.

All data were collected on a Thermo-Finnagan (San Jose, Calif.) LTQ-FTMS(a hybrid linear ion-trap with a 7 Tesla Fourier transform ion cyclotronresonance MS) with Xcalibur™ 2.0 and fitted with a New ObjectivePicoview 550 nanospray ionization source. Full scan data were collectedat 50,000 resolution (at 400 m/z) with a mass-to-charge ratio (m/z)range of 400 to 2000. The instrument was externally calibrated no lessthan 5 days prior to acquisition following manufacturer recommendedprotocol with caffeine, NRFA and Ultramark. All data were collectedusing data dependent scanning with multistage MS (MS/MS) usingcollision-induced dissociation (CID) with a 3 m/z isolation width,normalized collision energy of 35, and 30 millisecond activation in theion-trap MS (unit mass resolution) on the top five most abundantpeptides. Charge state screening and monoisotopic precursor selectionwere enabled. The acquisition has a 30 second dynamic exclusion using anm/z range of 0.01 low to 1.01 high for the exclusion list with anexclusion limit of 500 m/z values.

1.9 Database Searching.

Database searching was conducted using Thermo-Finnagan Bioworks 3.3.1SP1. The Human Refseq database was used (download November 2007 from theNational Center of Biological Information) for all searches. Prior tothe SEQUEST search, the Human Refseq database was indexed for Trypsin(KR), monoisotopic mass, fully enzymatic (cleavage at both sides),molecular weight range of 400-10000, 3 missed cleavage sites, andposttranslational modifications of oxidation of the methionines at15.99492 Da and alkylation of the cysteines at 57.02146 Da. Massaccuracy was set to 20 parts per million. For all fractions of eachpool, individual SEQUEST files were combined using the BioworksMulticonsensus report function. The rigorous SEQUEST search constraintswere set with a Delta CN≥0.100 and Xcorr vs. charge state of 1.9 for 1+,2.2 for 2+, and 3.75 for 3+ as suggested by the Human ProteomeOrganization (HUPO) (13) and 4.0 for 4+. The number of differentpeptides allowed for protein identification was set to one. The totalpeak areas were determined using the Bioworks algorithm PepQuan withparameters set to area, mass tolerance of 0.0100, minimum threshold of1000, number of smoothing points at 5, and including all proteins. Thefalse discovery rate was estimated to be less than 10%. Briefly, aconcatenated target-decoy database was created using the human Refseqdatabase. Results were searched against the concatenated database andfalse positives were estimated as twice the number of passing decoyfragments. The false discovery rate was determined by dividing the falsepositives by the sum of the true positives and false positives (74).

1.10 Statistical Analysis.

Plasma pools vary in the distribution of peptide abundance values due toexpected variability in the experimental process. To allow forcomparisons across pools, the median-centered natural logarithm ofpeptide abundance (peak area) within each pool was calculated tostandardize abundance values. Two approaches were used to handle thelarge amount of missing data which is typical for MS/MS-based proteomicstudies. In the first case, assuming missing data represent abundancevalues below the detection threshold, data were imputed to a value ofone-half the minimum intensity for each pool plus a small amount ofrandom error. In the second case, missing data were not imputed and thusno assumptions were made about the source of missing data, such astechnical error or the real absence or low abundance of protein inplasma. To identify peptides correlated linearly with the presence ofCOPD and an increasing rate of lung function decline, the study groupswere coded ordinally (control=1, SLW=2 and RPD=3) and regressed againstthe standardized peptide abundance values. Peptides were included ifobserved in at least three of the nine sample pools. The non-imputationmethod requires peptide presence in each of the three study groups forinclusion. Since the condition of normality of each peptide predictor inthe linear regression model cannot be guaranteed, empirically derivedp-values by a permutation test with 1,000 iterations were obtained.Multiple testing was corrected for by calculation of the false discoveryrate and the corresponding q-values were reported (14, 15, 16, 17).

1.11 Protein Annotation and Pathway Analysis.

Mapping of proteins to curated molecular pathways was conducted on KyotoEncyclopedia of Genes and Genomes (KEGG, at www.genome.jp/kegg/)(18-20). Pathway analysis was conducted with Ariadane Genomics' PathwayStudio™ software version 5.0 (Ariadne Genomics, Inc., Rockville, Md.).The analysis was manually filtered using the expanded pathway analysistool and limiting analysis to proteins.

1.12 Outcome

Offline SCX fractionation with RP-LC-ESI-MS/MS and robust databasesearching resulted in the observation of 1,758 unique peptides acrossall nine pooled samples. The filtering constraints for the imputationand non-imputation methods resulted in 1,133 and 973 peptides,respectively, for statistical analysis. At an FDR level of 10%, a totalof 17 peptides were significantly associated with lung function declinefor the imputation method, 20 peptides were significant for thenon-imputation method, and 7 of these peptides were identified by bothmethods (Table 2). The regression coefficient from the linear model,along with the associated q-value for each method where applicable, werealso presented in Table 2 for each unique peptide. A negative regressioncoefficient estimate indicated linearly decreasing peptide abundancelevels across the 3 study groups, from controls to SLW to RPD, while apositive estimate indicated a linear increase in peptide abundancelevels from controls to RPD.

TABLE 2Unique peptides differentially expressed across the 3 study groups:smokers without COPD, smokers with COPD with slow FEV₁ decline, and smokerswith COPD with rapid FEV₁ decline. Reported regression coefficientestimates for each peptide were significant at the 10% false discovery rate.Protein Name No Imputation Imputation Gene NCBI GI Number and RegressionRegression Peptide sequence symbol Accession/Version Number coefficient¹q-value coefficient¹ q-value Complement System -.GVFVLNK.- C3complement component C3 −0.235 <0.001 −3.211 <0.001gi: 4557385, NP_000055.1 K.KVFLDC*C*NYITELRR.Q C3complement component C3 0.575 <0.001 na na R.VVLVAVDK.G C3complement component C3 −2.323 <0.001 na na K.YFKPGM#PFDLM#VFVTN C3complement component C3 −0.863 0.094 −1.397 <0.001 PDGSPAYR.VR.IPIEDGSGEVVLSR.K C3 complement component C3 −2.998 0.094 na naK.PGFTIVGPNSVQC*Y CFH complement factor H −0.547 <0.001 na naHFGLSPDLPIC*K.E gi: 4504375, NP_000177.1 K.SSNLIILEEHLK.N CFHcomplement factor H −0.705 0.059 na na K.VKDISEVVTPR.F CFBcomplement factor B 0.603 <0.001 0.603 0.087 gi: 4502397, NP_001701.1R.RPASPISTIQPK.A C8G complement component 8, 0.801 <0.001 na nagamma polypeptide gi: 109731764, AAI13627.1 R.VPANLENVGFEVQTAED C6complement component 6 na na −2.450 <0.001 DLKTDFYK.Dgi: 4559406, NP_000056.1 R.HLVPGAPFLLQALVR.E C4A complement component 4Ana na −3.720 0.087 (Rodgers blood group) gi: 14577919, NP_009224.1R.LLEPHC*FPLSLVPTEFC* C7 complement component 7 na na −2.111 0.087PSPPALK.D gi: 45580688, NP_000578.2 Coagulation SystemR.LTIGEGQQHHLGGAK.Q FGG fibrinogen gamma chain 1.145 0.059 na nagi: 4503715, NP_000500.1 K.EKGEIQNILQK.V KLKB1kallikrein B, plasma (Fletcher 2.543 <0.001 na na factor) 1gi: 4504877, NP_000883.1 K.FEVQVTVPK.I A2M alpha 2 macroglobulin −0.329<0.001 na na gi: 4557225, NP_000005.1 R.KAAISGENAGLVR.A ITIH1inter-alpha (globulin) inhibitor 0.272 <0.001 na na H1gi: 4504781, NP_002206.1 K.GFPIKEDFLEQSEQLF SERPINF2serpin peptidase inhibitor, clade na na −2.183 0.087 GAKPVSLTGK.QF (alpha-2 antiplasmin, pigment epithelium derived factor), member 2gi: 260064050, NP_001159393 K.TSDQIHFFFAK.L SERPINC1serpin peptidase inhibitor, clade na na −4.296 0.087C (antithrombin), member 1 gi: 4502261, NP_000479.1 Anti-proteaseR.NLAVSQVVHK.A SERPINA3 serpin peptidase inhibitor, clade −0.226 <0.001na na A (alpha-1 antiproteinase, antitrypsin), member 3gi: 4501843, NP_001076.1 K.VLSALQAVQGLLVAQGR.A AGT Angiotensinogen−1.132 <0.001 −1.132 <0.001 gi: 4557287, NP_000020.1 K.DPTFIPAPIQAKT AGTAngiotensinogen −0.319 <0.059 na na Metabolic R.EYSGTIASEANTYLNSK.S APOBapo-B100 precursor 0.771 0.059 na na gi: 105990532, NP_000375.2K.DKDQEVLLQTFLDDASP APOB apo-B100 precursor na na −2.169 <0.001 GDKR.LR.ILGEELGFASLHDLQLL APOB apo-B100 precursor na na −2.646 0.087 GK.LK.KLVPFATELHER.L APOA4 apolipoprotein A-IV −0.458 <0.001 −0.458 <0.001gi: 4502151, NP000473.1 K.FLNVLSPR.G IGFBP3 insulin-like growth factorna na −3.154 <0.001 binding protein 3 gi: 114319031, AB163364.1R.VAGLLEDTFPGLLGLR.V IGFALS insulin-like growth factor na na −2.2140.087 binding protein, acid labile subunit isoform 1 precursorgi: 225579152, NP_001139478.1 Other R.C*EGPIPDVTFELLR.E A1BGalpha-1-B glycoprotein −1.037 0.059 −2.196 <0.001gi: 21071030, NP_570602.2 K.NGVAQEPVHLDSPAIK.H A1BGalpha-1-B glycoprotein 0.238 <0.001 0.238 0.087gi: 21071030, NP_570602.2 K.SEDC*FILDHGK.D GSNgelsolin (amyloidosis, Finnish na na −0.303 0.087type) gi: 55960302, CAI14416.1 na, not applicable. False discoveryrate > 10% for this analysis method. ¹A negative regression coefficientestimate indicates decreasing peptide abundance levels across the 3study groups, from controls to SLW to RPD,while a positive estimateindicates increasing peptide abundance levels across the 3 study groups.

The 30 unique peptides identified as differentially expressed across the3 study groups by linear regression mapped to 21 unique proteins. InTable 2 the peptides are grouped according to major function. Themajority of the identified peptides (17/30), representing 12 proteins,are involved in the complement cascade which, as part of the innateimmune system, promotes host defense mechanisms of bacterial lysis,phagocytosis, and immune cell recruitment and activation (21, 22).Regression analysis across the three study groups indicated a mixedpattern of over- and under-expression among the 17 complement-relatedpeptides.

SERPINA3, or serpin peptidase inhibitor, Glade A (alpha-1antiproteinase, antitrypsin), member 3, is relatively underexpressed inthe RPD group compared with the SLW group, and highest levels are in thecontrol group. SERPINA3 is a protease inhibitor and lower levels of thisprotein in the RPD support an imbalance in proteases/anti-proteases inthe RPD population. Certain allelic variants of SERPINA3 result inreduced protease inhibitor activity and have been associated with COPD(23-25).

Fibrinogen, kallikrein B and inter-alpha (globulin) inhibitor H1, allcomponents of the coagulation system, are relatively over expressed inthe COPD groups compared with the control group, with the highest levelsin the RPD group. Coagulation is a complex cascade involving plasmaproteins and platelets that results in blood clot formation (26).Circulating clotting factors and their proteases and antiproteasesregulate this process (27) and the coagulation system is thought to beinvolved in the thromboembolic complications associated with COPD andsmoking (28, 29, 30). Plasma levels of antithrombin (SERPINC1), acomponent of one of the principal intrinsic anticoagulant systems (31),and alpha-2 antiplasmin, a major regulator of intravascular fibrinolysis(32), are highest in the control group and lowest in the rapid FEV₁decline COPD group.

Alpha-2 antiplasmin is also involved in the renin-angiotensin system(RAS) as a critical regulator of angiotensin II-mediated vascularremodeling (Huo 2008). Angiotensinogen is an inactive circulatingsubstrate which is converted by renin to angiotensin I, the precursorpeptide in the classical RAS cascade (33). The circulating and localtissue renin-angiotensin systems are involved in vascular remodeling(34) and play pivotal pathophysiological roles in hypertension (35) anddiabetes (33). Experimental evidence suggests that oxidantstress-induced damage of lung microvascular endothelial cells incigarette smokers results in endothelial cell apoptosis, capillary loss,impaired angiogenesis, and profound airspace enlargement (29).

Expression of two insulin-like growth factor binding proteins (IGFBP3and IGFALS) is lowest in the RPD COPD group and highest in the controlgroup. This possibly reflects the lower levels of anabolic hormones,such as insulin-like growth factors and testosterone, found in chronicinflammatory muscle-wasting conditions such as COPD, chronic heartfailure, acquired immunodeficiency syndrome, and cancer (36, 37).

Three peptides mapping to apolipoprotein B100 had a mixed pattern ofdifferential expression across the study groups. Apolipoprotein B is themajor structural protein of very low- and low-density lipoproteins(VLDL, LDL), and apoB-containing lipoproteins transport cholesterol fromthe liver and gut to peripheral tissues (38). On the other hand,apolipoprotein A-IV is the major protein component of high-densitylipoproteins (HDL) which reverse transport cholesterol from theperiphery to the liver for excretion (38) and constitutes a potentendogenous inhibitor of lipid oxidation (39). Apolipoprotein A-IV isrelatively underexpressed in the COPD-RPD group compared with theCOPD-SLW and control groups.

Gelsolin (GSN) is an actin-binding protein involved in regulating hostresponse to cellular damage in bacterial sepsis (40). Two peptides withopposite directions of differential expression across the study groupsmapped to alpha-1B-glycoprotein, a plasma protein of unknown function.

Ariadne Genomics' Pathway Studio™ identified nine other proteins withmultiple connections to the 21 proteins identified as differentiallyexpressed across the three groups in this study (FIG. 1). These includedinsulin (INS, gi:307072, AAA59179.1), plasminogen (PLG, gi:387026,AAA60113.1), fibrinogen alpha (FGA, gi 11761629, NP_068657.1),coagulation factor 2 (F2, gi4503635 NP_000497.1), interleukin 6 (IL6,gi:10834984, NP_000591.1) and interleukin 1 beta (IL1B, gi:386816,AAA74137.1), signal transducer and activator of transcription 3 (STAT3,gi:21618340, NP_644805.1), cyclin dependent kinase 2 (CDK2, gi:30582481,AAP35467.1) and FAM3A (family with sequence similarity 3, member A,gi:57284179, CAI43239.1). Changes in the regulation of plasminogen andits role in coagulation have been associated with smoking and COPD (28).IL6 and IL1B promote the inflammatory response and both have beenobserved to be increased in the sputum (and IL6 in serum) of smokers andpersons with COPD (41, 42, 43, 30).

Furthermore, in a large genome-wide association study, a specific smallnucleotide polymorphism found in the IL6 receptor gene is identified asassociated with COPD (44). This suggests that IL6 signaling may be animportant pathway in COPD. An IL1B gene polymorphism has also beenlinked with COPD in a Korean population (45). In addition to the humandata linking ILB to COPD, a recent mouse model overexpressing IL1B inthe lung demonstrated similar tissue changes with inflammation, tissueremodeling and distal airway enlargement (46). Of the 9 additionalproteins found by pathway analysis, insulin, plasminogen, interleukin 6and interleukin 1 beta had the greatest number of interactions with the21 differentially expressed proteins observed, suggesting that the theseadditional proteins may represent common mechanistic pathways for COPDin cigarette smokers and for rate of lung function decline in COPD.

1.13 Summary

Using high-resolution MS proteomics and two rigorous statisticalmethods, multiple peptides were identified whose expression is linearlycorrelated across three groups of cigarette smokers classifiedspirometrically as having COPD with slow or no lung function decline,COPD with rapid decline and an unaffected control group. Thirty uniquepeptides, representing 21 proteins, differentiated the three groups. Themajority of the peptides observed are components of the complement orcoagulation cascades, consistent with the chronic and abnormalinflammatory response that is the hallmark of COPD and which is oftenassociated with a prothrombotic state (28). Ariadne Genomics' PathwayStudio™ analysis identified nine additional proteins that had multipleinteractions with the 21 observed proteins. Interestingly, the fourproteins with the greatest number of interactions with the 21differentially expressed proteins were insulin, plasminogen, interleukin6, and interleukin 1 beta, all of which have been previously associatedwith COPD or its complications. Insulin resistance, metabolic syndromeand diabetes have been shown to be associated with COPD (47, 48, 37).Both COPD and metabolic syndrome/insulin resistance appear to besystemic proinflammatory, prothrombotic disorders with significantassociated, and often common, comorbidities (47, 36, 48).

There is increasing evidence that the clinical features of COPDcorrelate poorly with airflow limitation as measured by spirometry (8)and, therefore, that spirometric parameters alone were inadequate asdiagnostic and prognostic biomarkers for this complex disease (73). Amore comprehensive evaluation using a multidimensional index (BODE) thatincorporates body mass index, airflow obstruction, dyspnea, and exercisecapacity, has been shown to be more predictive of mortality than FEV₁alone (49).

Although offline peptide fractionation enables the identification of agreater number of low-abundance plasma proteins, offline fractionationadds to the instrument time required for the data collection from eachsample. In this study, each pooled sample was fractionated offline into10 well-separated fractions, thus increasing the data collection time bya factor of 10. In the interest of reasonable data collection times, the18 plasma samples in each study group were grouped into 3 pools of 6samples each, for a total of 90 RP-LC-MS/MS samples in the study, eachrequiring approximately 2 hours per data collection (not includingblanks and quality controls collected every 10 samples). A disadvantageof sample pooling is the inability to collect information on individualvariation. However, a benefit is the dilution of undesired individualvariation (noise), and the amplification of any signal, by the factor ofdilution (i.e., 6 in this study).

Example 2: Differential Protein Expression Among Two Groups of AdultCigarette Smokers with Mild to Moderate COPD but Different Rates of LungFunction Decline

The plasma proteomes of 40 adult cigarette smokers with mild to moderateCOPD were analyzed. Subjects were clinically characterized as havingeither rapid decline (RPD, n=20) or slow to no decline (SLW, n=20) inFEV₁ over a five-year interval. The accurate mass and time (AMT) tagtechnology utilized is a comprehensive high-throughput proteomicapproach based upon a putative time and mass tag database (PMT), highresolution LC separations and high mass accuracy measurements usingFT-ICR MS with a 9.4-tesla magnetic field (50-53). Proteins identifiedas differentially abundant between the two clinical COPD categories (RPDvs. SLW) are exemplary biomarkers of rate of lung function decline inCOPD and are useful for monitoring and/or determining diseaseprogression in a subject

2.1 Subjects

Subjects were selected from the 624 participants in the Lung HealthStudy (LHS) at the University of Utah study center. LHS was aprospective, randomized, multicenter clinical study sponsored by theNational Heart, Lung, and Blood Institute (NHLBI) which enrolled maleand female otherwise healthy cigarette smokers, aged 35-60 years, withmild or moderate COPD during 1986-1989 (11). Lung function was measuredby spirometry at baseline, annually for 5 years, and once during1998-2001 (12). A subset of 244 participated in the Genetics of NicotineAddiction Project (GAP) during 2003-2004 in which lung spirometry andsmoking status were assessed and a plasma sample for proteomic analysiswas obtained.

Lung function was assessed as FEV₁ and FEV₁% predicted (e.g., adjustedfor age, sex, and height) (I). The annualized rate of lung functiondecline during the 5 years of LHS was calculated for each participant asthe slope of the linear regression of FEV₁% predicted. The 20 subjectswith the steepest rate of decline in FEV₁ (rapid decliners, RPD) and the20 subjects with the least steep or no annualized rate of decline inFEV₁ (slow decliners, SLW) were selected for proteomic analysis.Characteristics of the study groups are shown in Table 3. Over the first5 years of LHS, the rapid decliners had an average annual decrease inFEV₁ of 1.52% predicted/year, while the slow decliners had an averageincrease of 0.73% predicted/year. At the end of LHS, 5/20 (25%) of theRPD and 9/18 (50%) of the SLW participants no longer smoked. At the GAPassessment approximately 12 years later, 8/20 (40%) of the RPD and 11/18(61%) of the SLW participants no longer smoked. Two SLW subjects hadunacceptably low plasma peptide levels and were excluded from thisproteomic analysis.

TABLE 3 Characteristics of study subjects RPD SLW CharacteristicBaseline Year 5 GAP Baseline Year 5 GAP No. of subjects 20 18 Male, % 7067 Age, mean (SD) 64.9 (5.1)  64.4 (7.4) Cigarettes per day, 36.4(16.6)  26.5 (13.5) 15.9 (16.8) 30.2 (10.7) 10.6 (13.4)   7.2 (11.0)mean (SD) Years smoked, 30.5 (5.2)  — 43.0 (6.9)  29.1 (6.5)  — 35.8(9.3) mean (SD) FEV₁(L), 2.7 (0.57) 2.33 (0.63) 1.68 (0.59) 2.73 (0.63)2.73 (0.69)   2.4 (0.65) mean (SD) ΔFEV₁(mL/year), −75.0 (47.3)  4.9(43.7) mean (SD)^(a) FEV₁ % predicted, mean (SD) 75.3 (10.28)  67.7(12.89)  54.6 (16.95) 75.6 (10.0) 78.7 (12.18)  76.6 (14.6) ΔFEV₁ %predicted/year,   −1.52    0.73 mean (SD)^(b) FEV₁, forced expiratoryvolume in one second; RPD, FEV₁ rapid decliner group; SLW, FEV₁ slowdecliner group; GAP, Genetics of Nicotine Addiction Project, an averageof 17 years after baseline ^(a)Difference in FEV₁ (mL/year) at Year 5from baseline; for RPD vs. SLW, p < 0.001 ^(b)Difference in FEV₁ (%predicted) at Year 5 from baseline; for RPD vs. SLW, p < 0.0012.2 Plasma Sampling, Processing and MS Analysis

Plasma samples were obtained from each subject at least 2 h after eatingby venipuncture using a sodium citrated Vacutainer tube (BD, FranklinLakes, N.J.). Within 10 min of collection, blood was centrifuged at1500×g for 15 min at 2-6° C. The top-most plasma was removed andcentrifuged at 1500×g for an additional 15 min. Plasma samples wereshipped on dry ice, stored at −80° C. and thawed just before analysis.The plasma samples were analyzed using a comprehensive high-throughputproteomic approach, the accurate mass and time (AMT) tag technology, tofacilitate comprehensive high-throughput proteomic measurements. Thistechnology is based upon a putative mass and time (PMT) tag database,high resolution LC separations and high mass accuracy measurements usingFT-ICR MS with a 9.4-tesla magnetic field (50-53). This approachinvolved pooling a subset of randomly selected plasma samples afterdepletion of abundant proteins and digestion with trypsin. A standardshotgun proteomic analysis was performed where the pool was thenseparated by strong cation exchange and analyzed by reversed phasecapillary LC (rp-LC) coupled directly with an electrospray IT massspectrometer using a data-dependent MS/MS mode. The results were thenused to populate the PMT database. All samples were then analyzed usinga high resolution FT-ICR MS system. The data analysis incorporated boththe FT-ICR MS accurate mass measurements of intact proteins and the PMTdatabase. This two-stage approach utilized FT-ICR MS to validate peptideAMTs from the PMTs identified using the conventional MS/MS method. Thisapproach provided greater confidence in peptide identifications as wellas the foundation for later measurements without the need for MS/MSresulted in greater sensitivity and increased throughput (50-53).Details of each step were discussed below.

2.2.1 Depletion of Abundant Proteins from Plasma

The 12 most abundant proteins were depleted using GenWay Seppro 12spin-columns (GenWay Biotech, Inc., San Diego, Calif., nowProteomeLab-IgY-12, Beckman Coulter, Inc., Fullerton, Calif.) followingthe manufacturer's protocol. The removal of abundant proteins wasmonitored by SDS-PAGE.

2.2.2 In-Solution Tryptic Digestion of Plasma

TCA-precipitable protein from the depleted plasma samples was denaturedby the addition of urea to 8 M, thiourea to 2 M, DTT to 5 mM, andheating to 60° C. for 30 min. The sample was then diluted fourfold with100 mM ammonium bicarbonate, and calcium chloride was added to 1 mM.Methylated, sequencing-grade trypsin (Promega, Madison, Wis.) was addedat a substrate-to-enzyme ratio of 50:1 (mass:mass) and incubated at 37°C. for 15 h. Sample cleanup was achieved using a 1-mL SPE C₁₈ column(Supelco, Bellefonte, Pa.). The peptides were eluted from each columnwith 1 mL methanol and concentrated via Speed Vac. The samples werereconstituted to 10 μg/μL with 25 mM ammonium bicarbonate and frozen at−20° C. until analyzed.

2.2.3 Strong Cation Exchange Separation

From all 40 samples, six randomly selected plasma samples were depletedof abundant proteins, digested with trypsin as described above, andpooled. Strong cation exchange chromatography was performed on thepooled peptide sample utilizing a Synchropak S 300, 100×2 mmchromatographic column (Thermo Hypersil-Keystone, Bellefonte, Pa.). Aone-hour gradient was utilized at a flow rate of 200 μL/min withfractions collected every 2 min. The beginning solvent system was 25%acetonitrile and 75% water containing 10 mM ammonium formate at pH 3.0,adjusted with formic acid; the ending solvent system was 25%acetonitrile and 75% water containing 200 mM ammonium formate at pH 8.0.The peptide mixture was resuspended in 25% acetonitrile and 75% watercontaining 10 mM ammonium formate at pH 3.0 with formic acid prior toinjection. Fractions were lyophilized and stored at −20° C. until LCMS/MS analysis.

2.2.4 MS/MS Analysis of Peptides

Peptide samples were analyzed by reversed phase capillary LC (rp-LC)coupled directly with electrospray tandem mass spectrometers (ThermoFinnigan, models LCQ Duo and DecaXP, San Jose, Calif.). Chromatographywas performed on a 60-cm, 150-μm id×360-μm od capillary column(Polymicro Technologies, Phoenix, Ariz.) packed with Jupiter C₁₅5-μm-diameter particles (Phenomenex, Torrence, Calif.). A solventgradient was used to elute the peptides using 0.1% formic acid in water(solvent A) and 0.1% formic acid in acetonitrile (solvent B). Thegradient was linear from 0-5% solvent B in 20 min, followed by 5-70%solvent B in 80 min, and then 70-85% solvent B in 45 min. Solvent flowrate was 1.8 μL/min. The capillary LC system was coupled to a LCQ ITmass spectrometer (Thermo Finnigan, San Jose, Calif.) using an in-housemanufactured ESI interface, in which no sheath gas or makeup liquid wasused. The temperature of the heated capillary and the electrosprayvoltage was 200° C. and 3.0 kV, respectively. Samples were analyzedusing the data-dependent MS/MS mode over the m/z range of 300-2000. Thethree most-abundant ions detected in each MS scan were selected forcollision-induced dissociation.

2.2.5 Putative Mass and Time (PMT) Tag Database from Plasma Results

The raw LC-IT data from the pooled sample described above and data fromprevious multidimensional analysis (54) were reanalyzed to populate thePMT database using a PMT quality score of 1.0 [requires a minimumcross-correlation score (Xcorr) of 2] and a discriminate score of 0.5(52). This database was used to generate the AMT tag results.

2.2.6 FT-ICR Mass Spectrometry

A modified and enhanced Broker Daltonics 9.4-tesla FT-ICR MS (BrukerDaltonics Inc., Billerica, Mass.) was employed for the high-throughputproteomics, as described by Belov et al. (55). Briefly, the FT-ICR massspectrometer is combined with the capillary LC system and modified forconcurrent internal mass calibration and auto-sampling. Tryptic peptidesfor each individual sample were resuspended in mobile phase A (0.1% TFA)and analyzed separately using RP capillary LC coupled to an LSIinterface with a FT-ICR MS, as previously described (52). Analysis ofthe LC FT-ICR data was performed using in-house software tools thatincluded ICR-2LS (Pacific Northwest National Laboratory,http://omics.pnl.gov/software/ICR2LS.php). The initial analysis of rawLC FT-ICR data involved a mass transformation or de-isotoping step usingICR-2LS. To generate relative abundances for the peptides, each samplewas analyzed by FT-ICR in duplicate.

2.3 Database Searching

The SEQUEST algorithm (56) was run on each of the datasets against thehuman protein database from the National Center for BiotechnologyInformation (RefSeq release 10, March 2005). All data were collectedusing the multidimensional protein identification technology (MudPIT)approach developed by Yates and coworkers (57, 58). Briefly, allaccepted SEQUEST results have a delta Cn of 0.1 or greater. Peptideswith a +1 charge state were accepted if they were fully tryptic and havea Xcorr of at least 1.9. Peptides with a +2 charge state were acceptedif they were fully tryptic or partially tryptic and have an Xcorr of atleast 2.2. Peptides with +2 or +3 charge states with an Xcorr of atleast 3.0 or 3.75, respectively, were accepted regardless of theirtryptic state (58).

2.4 Data Analysis

When peptides were detected in some samples but not others, theundetected peptides were considered to be missing. On average, 60% ofdata (e.g., potential peptides) were missing across all quantitative MSruns. Missing values could be due, in part or in combination, to severalsources, including true absence of the peptide in blood plasma, anabundance of peptides at a level below the detection limit of MS, andfailure to correctly identify a peptide. Since the source of the missingdata was unclear, a single method of handling missing data would not beappropriate for all peptides. Therefore, differences in peptideabundance between RPD and SLW were assessed using three separatestatistical methods. In Method 1, missing values represent peptides notobserved. In Method 2, missing values were imputed to a value below thedetection threshold to account for low abundance peptides. In Method 3,a conservative proxy measure of peptide abundance was calculated thatavoids the imputation of data.

Replicates were averaged for Methods 1 and 2. Each run was standardizedby the respective median log base 2 intensity value to allow for directcomparisons across all samples. For Method 2, missing data was imputedto a value of one-half the minimum intensity for each run plus a smallamount of random error (SD=0.01). For Method 3, peptide abundance wascoded as an ordinal variable corresponding to the number of times thepeptide was observed in each replicate (e.g., 0, 1, or 2). This proxycoding correlates significantly with the observed quantitative outcome(r=0.45, p-value <0.0001).

Analysis was restricted to peptides present in at least 20% of thesamples. Tests for association of peptide abundance using the ordinalvariable with RPD-SLW group were carried out using exact logisticregression implemented in the R statistical software program (59). Theexact option was used to correct for small cell counts, and parameterestimates were obtained by Markov chain Monte Carlo 100,000 simulationsfollowing 1,000 burn-in iterations. For Methods 1 and 2, a two-sidedt-test was performed and empirically derived p-values were obtained by1,000 permutations of the data. The set of empirical p-values werecorrected for multiple testing by reporting the false discovery rate(14-17). All statistical analyses were performed using R version 2.5.1software (http://www.r-project.org).

2.5 Protein Annotation/Function

Mapping of proteins to curated molecular pathways was conducted on theKyoto Encyclopedia of Genes and Genomes (KEGG, on the world wide web atwww.genome.jp/kegg/) (18-20).

2.6 Outcome

2.6.1 Peptide/Protein Identification and Data Processing

A total of 3,549 non-redundant peptides were identified from 80independent MS runs (2 technical replicates per sample), representing533 proteins. Overall, the peptide abundance levels from technicalreplicates were very similar (mean R²=0.964, SD=0.054). The averagenumber of unique peptides detected in all samples was 1,362.46(SD=414.17). Two samples (4 MS runs) displayed lower-than-acceptablenumbers of peptides, and hence were omitted from further statisticalanalysis.

2.6.2 Peptide-Level Results

Peptide analysis revealed that 12, 49, and 10 peptides were significantat a false discovery rate of 5% for statistical Methods 1, 2, and 3,respectively. FIG. 2 illustrates the overlap on the peptide level amongthe three statistical methods.

2.6.3 Protein-Level Results

Since each of the statistical methods has its own strengths andweaknesses, the proteomic analysis was conducted on the proteinsassociated with the non-redundant peptides (Table 4) from all threemethods. The 33 proteins associated with the 55 peptides were found byat least one of the three statistical methods and hence were used forsubsequent network/pathway analysis. FIG. 2 also illustrates the overlapamong the statistical methods on the protein level.

TABLE 4Fifty-five unique peptides identified from statistical Methods 1, 2, or 3 as differentially expressedbetween FEV₁ rapid (RPD) and slow (SLW) decliner subjects with chronic obstructive pulmonary diseaseNCBI Model coefficients^(a) Genbank Gene Method Method Method PeptideAccession symbol Gene name 1 2 3 GAAANLELIFVGPQHAGNYR NP_570602.2 A1BGalpha 1B-glycoprotein 0 −1.50 0 precursor LHDNQNGWSGDSAPVELILSDNP_570602.2 A1BG alpha 1B-glycoprotein 0 2.67 0 ETLPAPEFSPEPESGRprecursor VTLTCVAPLSGVDFQLR NP_570602.2 A1BG alpha 1B-glycoprotein 0−2.48 −2.77 precursor ASVSVLGDILGSAMQNTQN NP_000005.1 A2Malpha-2-macroglobulin 0 −2.24 0 precursor DSFHLDEQFTVPVEMMQARNP_000925.1 SERPIN alpha-2-plasmin inhibitor 1.14 1.39 0 F2EATEGKIQEFLSGLPEDTVLLL NP_000925.1 SERIPIN alpha-2-plasmin inhibitor 0−3.32 −1.99 LNAIHFQGFWR F2 GFPRGDKLFGPDLK NP_000925.1 SERPINalpha-2-plasmin inhibitor 0 −0.88 0 F2 AGANVLAKNK NP_055757.1 ANKRD6ankyrin repeat domain 6 0 2.37 1.81 PYADEFK NP_000473.1 APOA4apolipoprotein A-IV 0 1.19 0 precursor ALYWVNGQVPDGVSK NP_000375.1 APOBapolipoprotein B precursor 0 1.80 0 IAELSATAQEIIK NP_000375.1 APOBapolipoprotein B precursor 0.94 0 0 LLLQMDSSATAYGSTVSKR NP_000375.1 APOBapolipoprotein B precursor −1.82 0 0 KLISVDTEHSNIYLQNGPDR NP_000087.1 CPceruloplasmin precursor 0 1.80 0 MFGNLQGLTMHVGDEVNWYL NP_000087.1 CPceruloplasmin precursor 0 2.00 0 MGMGNEIDLHTVHFHGHSFQY K TLLSNLEEAKNP_001822.2 CLU clusterin isoform 1 0 −0.86 0 ETYDFDIAVLR NP_000495.1F10 coagulation factor X 0 −1.17 0 preproprotein SSNNPHSPIVEEFQVPYNKNP_001725.1 C1S complement component 1, 0 2.65 2.02 s subcomponentAGDFLEANYMNLQR NP_000055.1 C3 complement component 3 0.84 0.84 0precursor PLSWDIPELVNMGQWK NP_000055.1 C3 complement component 3 0 1.890 precursor QKPDGVFQEDAPVIHQEMIGG NP_000055.1 C3 complement component 30 2.19 0 LR precursor QLYNVEATSYALLALLQLKDF NP_000055.1 C3complement component 3 0 2.78 0 DFVPPVVR precursor RQGALELIK NP_000055.1C3 complement component 3 −0.63 0 0 precursor SPYQIHFTK NP_000055.1 C3complement component 3 0 −1.22 0 precursor SYTVAIAGYALAQMGR NP_000055.1C3 complement component 3 0 2.41 0 precursor NPSDPMPQAPALWIETTAYALNP_001002029 C4B complement component 0 −2.23 0 LHLLLHEGKAEMADQAAAWL4B preproprotein TR PGNSDPNMIPDGDFNSYVR NP_001002029.1 C4Bcomplement component 1.13 0 0 4B preproprotein EKFSDASYQSINIPVTQNMVPSNP_001726.1 C5 complement component 5 0 1.41 0 SR FSDASYQSINIPVTQNMVPSSRNP_001726.1 C5 complement component 5 0 1.55 0 AKDLHLSDVFLK NP_000056.1C6 complement component 6 0 −0.89 0 precursor DISEVVTPR NP_001701.1 CFBcomplement factor B 0 3.53 2.63 preproprotein HVIILMTDGLHNMGGDPITVIDNP_001701.1 CFB complement factor B 0 3.73 2.39 EIRDLLYIGK preproproteinAVPHPDSQPDTIDHDLLLLQLS NP_001919 CFD complement factor D 0 1.24 0 EKpreproprotein NDFTWFK NP_000177.1 CFH complement factor H 0 −1.46 0isoform a precursor YQIWTTVVDWIHPDLKR NP_000195.1 CFIcomplement factor 1 0 −1.60 0 preproprotcin PNMIDAATLK NP_000500.1 FGGfibrinogen, gamma chain −1.42 0 0 isoform gamma-A TYNPDESSKPNMIDAATLKNP_000500.1 FGG fibrinogen, gamma chain 0 −2.39 0 isoform gamma-AGATYNIIVEALKDQQR NP_002017 FN1 fibronectin 1 isoform 3 0 3.00 2.00preproprotein TPFVTHPGYDTGNGIQLPGTSG NP_002017 FN1fibronectin 1 isoform 3 0 2.19 1.84 QQPSVGQQMIFEEHGFRR preproproteinAGALNSNDAFVLK NP_000168.1 GSN gelsolin isoform a 1.18 1.49 0 precursorIEGSNKVPVDPATYGQFYGGD NP_000168.1 GSN gelsolin isoform a 1.27 1.57 0SYIILYNYR precursor AAISGENAGLVR NP_002206.1 ITIH1inter-alpha (globulin) 0 −3.74 0 inhibitor H1 AHNVVTMR NP_002208.1 ITIH3inter-alpha (globulin) 0 −1.53 0 inhibitor H3 ANTVQEATFQMELPKNP_002209.2 ITIH4 inter-alpha (globulin) 0 1.99 0 inhibitor H4RLGVYELLLK NP_002209.2 ITIH4 inter-alpha (globulin) 0 −2.75 0inhibitor H4 LWAYLTINQLLAER NP_002207.1 ITIH2 inter-alpha globulin 0−1.80 0 inhibitor H2 polypeptide SLPLLMDSV1QALAELEQKVPA NP_443122.2PG1.YR peptidoglycan recognition 0 −3.53 −3.41 AK P2 protein 2 precursorEIIIHQNYK NP_000883.1 KLKB1 plasma kallikrein B1 0 3.01 0 precursorNNEEYLALIFEKGGSYLGR NP_002817.2 QSOX1 quiescin Q6 sulfhydryl 0 −1.75 0oxidase 1 isoform a ELTPEVLQEWLDELEEMMLVV NP_000479.1 SERPINserine (or cysteine) 0 2.56 0 HMPR C1 proteinase inhibitor, cladeC (antithrombin), member L antithrombin FATTFYQHLADSKNDNDNIFLSNP_000479.1 SERPIN serine (or cysteine) 0 3.29 0 PLSISTAFAMTK C1proteinase inhibitor, clade C (antithrombin), member L antithrombinLYGSEAFATDFQDSAAAK NP_001076.1 SERPIN serpin peptidase inhibitor, 0.880.88 0 A3 clade A, member 3 NLAVSQVVHK NP_001076.1 SERPINserpin peptidase inhibitor, −0.59 0 0 A3 clade A, member 3 KALQTEMARNP_000233.1 MBL2 soluble mannose-binding 0 −1.51 0 lectin precursorGILGKDVSGFSDPYCLLG NP_954712.1 UNC13 unc-13 homolog D 0 0.79 2.58 DDWHGVPGQVDAAMAGR NP_000629.2 VTN vitronectin precursor 0.79 0.79 0^(a)Positive coefficient indicates more peptide in RPD vs. SLW; negativecoefficient indicates less peptide in RPD vs. SLW; non-zero coefficientswere significant at a false discovery rate <5%

This example used an untargeted global proteomic approach to investigatenovel plasma proteins associated with the rate of FEV₁ decline incigarette smokers with COPD. Using three rigorous statistical methods,multiple peptides were found that discriminated between COPD subjectswith rapid and slow decline in lung function. The combined analysisidentified 55 peptides that putatively correspond to 33 proteins. Themajority of these proteins reside in the coagulation and complementcascades, as identified by KEGG (18-20) (FIG. 3). Of these proteins,only serum fibrinogen has been previously linked to an accelerateddecline of lung function in COPD subjects (60-62). These proteinsrepresent biomarkers for lung function decline in CORD.

2.6.4 Complement.

The complement system, a complex, multi-protein cascade, is part of theinnate immune system and plays an important role in host defenses bypromoting bacterial lysis, phagocytosis, and immune cell recruitment andactivation (21, 22). In the present example, 12 of the identifiedproteins are known to be involved in the complement system (FIG. 3).Chronic inflammation and an abnormal inflammatory response to noxiousinhaled particles or gases were considered to be key pathogenicmechanisms in COPD (1, 60, 63, 64). Exacerbations of CORD and decline inlung function have been linked to bacterial and viral pulmonaryinfections (33-35). It is therefore possible that the differentialcomplement activity suggested between the RPD and SLW in this study isthe result of an ongoing or recurrent microbial stimulus in the lungs ofthe rapid decliners, leading to direct complement activation as well asactivation secondary to the antibody response to these microbes by theadaptive immune system. A boosted adaptive immune response to viralinfections and bacterial colonization of the airways can also result insome subjects with COPD, even after smoking cessation. Molecular mimicrybetween foreign microbial antigens and self-determinants can result inself-reactivity with autoantibody formation to autoantigens andsubsequent complement activation (6, 65). Chronic inflammation in COPDis associated with increased levels of interleukin (IL)-6, whichsubsequently increases hepatic synthesis of proinflammatory andprothrombotic proteins such as C-reactive protein, fibrinogen and othercoagulation factors (4, 66). A recent genetic association study foundthat the IL-6R locus is associated with COPD (67). IL-6 expression,which is also increased in cigarette smokers (30, 43), has been reportedto influence complement 3 and 4 gene expression (68).

In addition to the complement pathway, other proteins were identifiedthat have been shown to play a role in bacterial defenses. Peptidoglycanrecognition protein 2 is a bacterial binding protein that is produced bythe liver and is part of the non-complement-related innate immune system(69). It may reflect a greater bacterial load in COPD subjects withaccelerated lung function decline. Gelsolin is an actin-binding plasmaprotein that has been reported to be important in regulating the hostresponse to cellular damage that occurs during bacterial sepsis (40).Another identified protein, inter-alpha-inhibitor, plays a role incoagulation during endotoxic shock (70). The identification of theseproteins and components of the complement pathway as differentiallyexpressed between rapid and slow FEV₁ decliners in COPD suggests thatbacterial host defenses may be playing a role in the progression andseverity of COPD.

2.6.5 Coagulation

Coagulation involves a complex cascade of plasma protein and plateletactivation that results in blood clot formation (26). This process isregulated by circulating clotting factors and their proteases andantiproteases (27). In this study, 12 interleukinoteins that wereinvolved in coagulation were identified as differentially expressedbetween RPD and SLW (FIG. 3). COPD is associated with higher levels ofprocoagulant proteins in the blood (71,72). Coagulation may play animportant role in COPD progression and has been implicated in thethromboembolic complications associated with COPD and smoking (30, 28,29). Except for fibrinogen, described above, the proteins identified inthe present study differed from those previously reported.

The Use of Additional Protein Biomarkers

The proteins identified in Examples 1 and 2 may be employed with otherprotein biomarkers of lung function for use in the methods describedherein, such as methods of diagnosing lung disease, providing aprognosis to a subject having lung disease, and/or distinguishingindividuals with rapid or slow decline in lung function. The proteinsidentified in Examples 1 and 2 may also be employed with other proteinbiomarkers of lung function in forming compositions for use conductingthe methods described herein. A number of such protein biomarkers havebeen described. In one embodiment such protein biomarkers include thoseprotein biomarkers capable of use in distinguishing between subjectswith rapidly declining pulmonary function and slowly declining pulmonaryfunction. One group of such markers is listed in Table 5a and wasdescribed in WO 20081003066 A2, which is hereby incorporated byreference. Those proteins described in WO 20081003066 A2 as having atwo-fold or greater difference in abundance between slow declineconditions and rapid decline conditions are listed in Table 5b. In oneembodiment, any number of the proteins of either Table 5a or 5b can beemployed in the methods described herein with proteins identified in thepresent study.

TABLE 5a Proteins Identified in WO20081003066 A2 NCBI GI and AccessionNumber/Verison R Protein Description gi|4501987|ref|NP_001124.1| afaminprecursor; alpha-albumin [Homo sapiens] gi|4502027|ref|NP_000468.1|albumin precursor; PRO0883 protein [Homo sapiens]gi|21071030|ref|NP_570602.2| alpha 1B-glycoprotein [Homo sapiens]gi|4501843|ref|NP_001076.1| alpha-1-antichymotrypsin, precursor;alpha-1-antichymotrypsin; antichymotrypsin [Homo sapiens]gi|4557225|ref|NP_000005.1| alpha-2-macroglobulin precursor [Homosapiens] gi|11386143|ref|NP_000925.1| alpha-2-plasmin inhibitor;alpha-2-antiplasmin [Homo sapiens] gi|4557287|ref|NP_000020.1|angiotensinogen precursor; angiotensin II precursor;pre-angiotensinogen; angiotensin I [Homo sapiens]gi|4557321|ref|NP000030.1| apolipoprotein A-I precursor [Homo sapiens]gi|4502149|ref|NP001634.1| apolipoprotein A-II precursor [Homo sapiens]gi|4502151|ref|NP000473.1| apolipoprotein A-IV precursor [Homo sapiens]gi|4502153|ref|NP_000375.1| apolipoprotein B precursor; apoB-100;apoB-48 [Homo sapiens] gi|4502157|ref|NP_001636.1| apolipoprotein C-Iprecursor [Homo sapiens] gi|4557325|ref|NP_000032.1| apolipoprotein Eprecursor; apolipoprotein E3 [Homo sapiens] gi|4557327|ref|NP_000033.1|beta-2-glycoprotein I precursor [Homo sapiens]gi|4557373|ref|NP_000051.1| biotinidase precursor [Homo sapiens]gi|4502517|ref|NP_001729.1| carbonic anhydrase I; carbonic dehydratase[Homo sapiens] gi|4503011|ref|NP_001299.1| carboxypeptidase N,polypeptide 1, 50 kD precursor [Homo sapiens]gi|4557485|ref|NP_000087.1| ceruloplasmin (ferroxidase); Ceruloplasmin[Homo sapiens] gi|42716297|ref|NP_001822.2| clusterin isoform 1;complement-associated protein SP-40 [Homo sapiens]gi|4503635|ref|NP_000497.1| coagulation factor II precursor; prothrombin[Homo sapiens] gi|4503625|ref|NP_000495.1| coagulation factor Xprecursor; prothrombinase; factor Xa [Homo sapiens]gi|4557379|ref|NP_000053.1| complement component 1 inhibitor precursor[Homo sapiens] gi|4502493|ref|NP_001724.1| complement component 1, rsubcomponent [Homo sapiens] gi|7706083|ref|NP_057630.1| complementcomponent 1, r subcomponent-like precursor; complement Clr-likeproteinase; Clr-like serine protease analog [Homo sapiens]gi|4502495|ref|NP_001725.1| complement component 1, s subcomponent [Homosapiens] gi|14550407|ref|NP_000054.2| complement component 2 precursor;C3/C5 convertase [Homo sapiens] gi|4557385|ref|NP_000055.1| complementcomponent 3 precursor; acylation-stimulating protein cleavage product[Homo sapiens] gi|4502503|ref|NP_000706.1| complement component 4binding protein, alpha; Complement component 4- binding protein, alphapolypeptide; complement component 4-binding protein, alpha [Homosapiens] gi|50345296|ref|NP_001002029.1| complement component 4Bpreproprotein; Chido form of C4; basic C4; C4A anaphylatoxin [Homosapiens] gi|38016947|ref|NP_001726.2| complement component 5 [Homosapiens] gi|4559406|ref|NP_000056.1| Complement component 6 precursor[Homo sapiens] gi|45580688|ref|NP_000578.2| complement component 7precursor [Homo sapiens] gi|4557389|ref|NP_000553.1| complementcomponent 8, alpha polypeptide precursor [Homo sapiens]gi|4502511|ref|NP_001728.1| complement component 9 [Homo sapiens]gi|4502397|ref|NP_001701.1| complement factor B preproprotein; C3proactivator; C3 proaccelerator; glycine- rich beta-glycoprotein; C3/C5convertase [Homo sapiens] gi|4504375|ref|NP_000177.1| complement factorH; H factor-1 (complement); factor H-like 1; H factor 2 (complement); Hfactor 1 (complement) Homo sapiens] gi|11761629|ref|NP_068657.1|fibrinogen, alpha chain isoform alpha preproprotein [Homo sapiens]gi|11761631|ref|NP_005132.1| fibrinogen, beta chain preproprotein [Homosapiens] gi|4503715|ref|NP_000500.1| fibrinogen, gamma chain isoformgamma-A precursor [Homo sapiens] gi|47132557|ref|NP_997647.1|fibronectin 1 isoform 1 preproprotein; cold-insoluble globulin;migration- stimulating factor [Homo sapiens] gi|4504165|ref|NP_000168.1|gelsolin isoform a [Homo sapiens] gi|11321561|ref|NP_000604.1| hemopexin[Homo sapiens] gi|4504355|ref|NP_000176.1| heparin cofactor II [Homosapiens] gi|4504579|ref|NP_000195.1| I factor (complement) [Homosapiens] gi|21489959|ref|NP_653247.1| immunoglobulin J chain [Homosapiens] gi|4504781|ref|NP_002206.1| inter-alpha (globulin) inhibitorH1; inter-alpha (globulin) inhibitor, H1 polypeptide [Homo sapiens]gi|4504783|ref|NP_002207.1| inter-alpha (globulin) inhibitor H2;inter-alpha (globulin) inhibitor, H2 polypeptide [Homo sapiens]gi|10092579|ref|NP_002208.1| inter-alpha (globulin) inhibitor H3;Inter-alpha (globulin) inhibitor, H3 polypeptide; pre-alpha (globulin)inhibitor, H3 polypeptide [Homo sapiens] gi|31542984|ref|NP_002209.2|inter-alpha (globulin) inhibitor H4 (plasma Kallikrein-sensitiveglycoprotein); Inter-alpha (globulin) inhibitor, H4 polypeptide;inter-alpha (globulin) inhibitor, H polypeptide-like 1 [Homo sapiens]gi|10835141|ref|NP_000563.1| interleukin 10 precursor; cytokinesynthesis inhibitory factor [Homo sapiens] gi|4504893|ref|NP_000884.1|kininogen 1; alpha-2-thiol proteinase inhibitor; bradykinin [Homosapiens] gi|4505047|ref|NP_002336.1| lumican [Homo sapiens]gi|33188445|ref|NP_036222.3| microfilament and actin filamentcross-linker protein isoform a; actin cross-linking factor; 620 kDaactin binding protein; macrophin 1; trabeculin-alpha; actin cross-linking family protein 7 [Homo sapiens] gi|19923106|ref|NP_000437.3|paraoxonase 1; Paraoxonase [Homo sapiens] gi|21361845|ref|NP_443122.2|peptidoglycan recognition protein L precursor [Homo sapiens]gi|4504877|ref|NP_000883.1| plasma kallikrein B1 precursor; kallikrein3, plasma; Kallikrein, plasma; kallikrein B plasma; Fletcher factor[Homo sapiens] gi|4505881|ref|NP_000292.1| plasminogen [Homo sapiens]gi|151465432|ref|XP_376519.2| PREDICTED: ankyrin repeat domain 6 [Homosapiens] gi|42662334|ref|XP_375941.1| PREDICTED: FLJ45139 protein [Homosapiens] gi|42656986|ref|XP_098238.8| PREDICTED: SH3 domain protein D19[Homo sapiens] gi|51464068|ref|XP_209550.4| PREDICTED: similar toCarboxypeptidase N 83 kDa chain (Carboxypeptidase N regulatory subunit)[Homo sapiens] gi|51458647|ref|XP_497680.1| PREDICTED: similar toprohibitin [Homo sapiens] gi|51460685|ref|XP_497833.1| PREDICTED:similar to SULT6B1 [Homo sapiens] gi|4506117|ref|NP_000304.1| protein S(alpha); Protein S, alpha [Homo sapiens] gi|13325075|ref|NP_002817.2|quiescin Q6 [Homo sapiens] gi|5803139|ref|NP_006735.1| RBP4 gene product[Homo sapiens] gi|21361198|ref|NP_000286.2| serine (or cysteine)proteinase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin),member 1; protease inhibitor 1 (anti-elastase), alpha-1-antitrypsin[Homo sapiens] gi|4507377|ref|NP_000345.1| serine (or cysteine)proteinase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin),member 7; thyroxine-binding globulin; thyroxin-binding globulin [Homosapiens] gi|4502261|ref|NP_000479.1| serine (or cysteine) proteinaseinhibitor, clade C (antithrombin), member 1; antithrombin III [Homosapiens] gi|39725934|ref|NP_002606.3| serine (or cysteine) proteinaseinhibitor, Glade F (alpha-2 antiplasmin, pigment epithelium derivedfactor), member 1; pigment epithelium-derived factor [Homo sapiens]gi|4502133|ref|NP_001630.1| serum amyloid P component precursor;penlaxin-related; 9.5S alpha-1- glycoprotein [Homo sapiens]gi|7382460|ref|NP_001031.2| sex hormone-binding globulin; Sexhormone-binding globulin (androgen binding protein) [Homo sapiens]gi|4557739|ref|NP_000233.1| soluble mannose-binding lectin precursor;Mannose-binding lectin 2, soluble (opsonic defect); mannose bindingprotein [Homo sapiens] gi|4507659|ref|NP_003283.1| translocated promoterregion (to activated MET oncogene); Tumor potentiating region(translocated promoter region) [Homo sapiens]gi|46195765|ref|NP_954712.1| unc-13 homolog D [Homo sapiens]gi|32483410|ref|NP_000574.2| vitamin D-binding protein precursor;vitamin D-binding alpha-globulin [Homo sapiens]gi|18201911|ref|NP_000629.2| vitronectin precursor; serum spreadingfactor; somatomedin B; complement S- protein; epibolin [Homo sapiens]

TABLE 5b Proteins Identified in WO20081003066 A2 having twofold orgreater difference in abundance between slow and rapid decline in lungfunction Anti-Log (Rapid Average Rapid NCBI GI decline conditionsdecline conditions Number of Reference Protein vs. Slow decline to Slowdecline Standard Significant Number Description conditions conditionsRatio Deviation Peptides 4501843 Antichymotrypsin 0.87 0.83 0.05 24557225 Alpha-2-macroglobulin 0.88 1.05 0.48 4 4502153 Apolipoprotein B1.48 1.22 0.21 17 4557485 Ceruloplasmin 0.97 0.82 0.34 5 4557385Complement component 3 0.64 0.71 0.22 15 11761629 Fibrogen, alpha chainisoform 1.24 1.29 0.37 6 11761631 Fibrogen, beta chain 1.41 1.23 0.30 54503715 Fibrogen, gamma chain isoform 1.21 1.24 0.50 5 47132557Fibronectin 1 isoform 1 0.75 0.63 0.17 2 4504165 Gelsolin isoform a 0.760.85 0.30 4 4504893 Kininogen 1; bradykinin 1.20 1.27 0.10 2 4504877Plasma kallikrein B1; kallikrein 0.46 1 3, plasma 21361198 Serine (orcysteine) proteinase 1.60 1.37 0.15 4 inhibitor; alpha-1-antitrypsin4502133 Serum amyloid P component 1.26 1.23 0.04 2 32483410 VitaminD-binding protein 0.86 1

Another group of protein biomarkers that are capable of distinguishingbetween subjects with rapidly declining pulmonary function and slowlydeclining pulmonary function, are described in WO 2009/114292 A1, andlisted in Table 6 parts a-d. In some embodiments, any number of theproteins identified in Table 6, or in any of its separate subsections(6a, 6b, 6c or 6d), may be employed in the methods described herein withany number of the proteins identified in the present study and/or incombination with any number of the proteins identified in Tables 5a or5b.

TABLE 6(a) Proteins identified in Signatures as disclosed in WO20081003066 A2. The listed accession numbers correspond to entrieswithin the National Center for Biotechnology Information (NCBI) databasemaintained by the National Institutes of Health. Human polynucleotideHuman protein Protein Other names accession no. (NCBI) accession no.(NCBI) Apolipoprotein H Beta-2 glycoprotein I NM_000042 NP_000033 CD40CD40L receptor NM_001250 NP_001241 Haptoglobin Hp2-alpha NM_005143NP_005134 IL-8 Interleukin-8 NM_000584 NP_000575 MCP-1 CCL2 NM_002982NP_002973 TNF-RII TNFRSF1B NM_001066 NP_001057 Apolipoprotein CIII Apoc3NM_000040 NP_000031 GM-CSF Colony stimulating NM_000758 NP_000749 factor2 IgA Immunoglobulin type A BC087841 AAH87841 MIP-1α CCL3 NM_002983NP_002974 Tissue factor Coagulation factor III NM_001993 NP_001984 TNF-αTNF superfamily NM_000594 NP_000585 member 2 α1-antitrypsin Serpin A1NM_000295 NP_000286 CRP C-reactive protein NM_000567 NP_000558Fibrinogen FGA NM_000508 NP_000499 MDC CCL22 NM_002990 NP_002981 sVCAM-1Soluble VCAM-1 NM_001078 NP_001069 IL-4 Interleukin-4 AF395008 AAK71324

TABLE 6b Differences in plasma markers between COPD rapid decliners andindividuals without lung disease Marker Fold change p value (FPR) qvalue (FDR) Alpha-1- antitrypsin 1.11 0.0238 0.062 Alpha fetoprotein1.38 0.0498 0.094 Apolipoprotein A1 1.38 0.0020 0.017 Apolipoprotein H1.15 0.0029 0.019 Carcinoembryonic 1.75 0.0022 0.017 antigen Eotaxin2.64 0.0007 0.008 Factor VII 1.16 0.0448 0.091 Fibrinogen 1.18 0.02310.062 GM-CSF 1.51 0.0061 0.026 Haptoglobin 2.02 0.0115 0.034 IL-10 1.540.0116 0.034 IL-13 1.69 0.0086 0.031 IL-1 alpha 1.16 0.0336 0.079 IL-31.46 0.0496 0.094 IL-4 4.21 <0.0001 0.000 IL-5 1.59 0.0041 0.023 IL-72.16 0.0044 0.023 IL-8 1.20 0.0398 0.088 MCP-1 1.51 <0.0001 0.001 Serumamyloid P 1.28 0.0049 0.023 Tissue factor 1.19 0.0410 0.088 TNF-RII−1.19 0.0071 0.028 Thrombopoietin 7.55 0.0117 0.034 sVCAM-1 −1.20 0.00020.003 VEGF 1.18 0.0301 0.075 NCBI Accession Numbers and NCBI GI Numbersfor the markers appearing in table 6b are as follows. Marker Accessionnumber and GI alpha-I - AAB59495.1 GI:177831 antitrypsin alphafetoprotein AAB58754.1 GI:178236 apolipoprotein A1 AAD34604.1 GI:4960066apolipoprotein H AAA51766.1 GI:178857 Carinoembryonic CAA44076.1GI:1877203 antigen Eotaxin CAB07027.1 GI:2462478 Factor VII AAA51983.1GI:180334 Fibrinogen CAA50740.1 GI:394794 GM-CSF AAA52578.1 GI:183364Haptoglobin AAA88080.1 GI:386783 IL-10 NP 000563.1 GI:10835141 IL-13 NP002179.2 GI:26787978 IL-1 alpha CAA27448.1 GI:33786 IL-3 AAC08706.1GI:3002475 IL-4 AAH70123.1 GI:47123367 IL-5 NP 000870.1 GI:4504671 IL-7AAH47698.1 GI:29126905 IL-8 AAH13615.1 GI:15488984 MCP-1 AAB29926.1GI:545465 Serum amyloid P BAA00060.1 GI:220068 Tissue factor AAA61152.1GI:339506 TNF-R11 NP 001057.1 GI:4507577 Thrombopoietin AAB33390.1GI:914226 sVCAM-1 VGEF CAC19513.2 1:220732299

TABLE 6c Differences in plasma markers between COPD slow decliners andindividuals without lung disease Marker Fold change p value (FPR) qvalue (FDR) Apolipoprotein H 1.16 0.0230 0.696 Cancer antigen 19.9 2.290.0078 0.563 Eotaxin 1.68 0.0358 0.696 VEGF 1.11 0.0545 0.696 NCBIAccession Numbers and NCBI GI Numbers for the markers appearing in table6c are as follows. Marker Accession number and GI apolipoprotein HAAA51766.1 GI:178857 Cancer antigen 19.9 none found Eotaxin CAB07027.1GI:2462478 VEGF CAC19513.2 GI:220732299

TABLE 6d Differences in plasma markers between COPD rapid and slowdecliners. Marker Fold change p value (FPR) q value (FDR) Cancer antigen19.9 −1.43 0.0355 0.300 IgA −1.57 0.0120 0.157 IL-4 1.27 0.0008 0.054IL-5 1.48 0.0139 0.157 Insulin −5.86 0.0165 0.160 MCP-1 1.44 0.00260.089 MDC 1.28 0.0422 0.300 MIP-1 alpha −1.26 0.0468 0.300 Tissue factor1.32 0.0125 0.157 sVCAM-1 −1.31 0.0043 0.098 NCBI AccessionNumbers andNCBI GI Numbers for the markers appearingin table 6d are as followsMarker Accession number and GI Cancer antigen 19.9 IgA CAA10818.1GI:2632187 IL-4 AAH70123.1 GI:47123367 IL-5 NP_000870.1 GI:4504671Insulin AAA59179.1 GI:307072 MCP-1 AAB29926.1 GI:545465 MDC AAB29191.1GI:455835 MIP-1 alpha P10147.1 GI:127078 Tissue factor AAA61152.1GI:339506 sVCAM-1

Among the protein biomarkers identified herein, a group of proteinbiomarkers not described in either WO20081003066 A2 or WO 2009/114292 A1have been identified. Those protein biomarkers, which include insulin,plasminogen, interleukin 6, interleukin 1 beta (IL1 B), signaltransducer and activator of transcription 3 (STAT3), cyclin dependentkinase 2 (CDK2) and FAM3A (family with sequence similarity 3, member A)which were identified using Ariadne Genomics' Pathway Studio™, arelisted in Table 7.

TABLE 7 GI Number and Protein NCBI Accession/Version SEQ ID NO:complement component 4A (Rodgers blood group) GI:14577919, NP_009224 1(Precursor) serpin peptidase inhibitor, clade A (alpha-1 GI:4501843,NP_001076.1 2 antiproteinase, antitrypsin), member 3 complementcomponent 8, gamma polypeptide GI:109731764, AAI13627.1 3 serpinpeptidase inhibitor, clade F (alpha-2 GI:260064050, NP_001159393 4antiplasmin, pigment epithelium), insulin-like growth factor bindingprotein 3 GI:114319033, DQ884398.1 5 insulin-like growth factor bindingprotein, GI:4826772, NP_004961.1 6 acid labile subunit gelsolin(amyloidosis, Finnish type) GI:119607896, EAW87490.1 7 complement factorD GI:42544239, NP_001919.2 8 fibronectin 1 isoform 3 preproproteinGI:16933542, NP_002017.1 9 Insulin GI:307072, AAA59179.1 10 plasminogenGI:387026, AAA60113.1 11 Interleukin 6 GI:10834984, NP_000591.1 12interleukin 1 beta GI:386816, AAA74137.1 13 signal transducer andactivator of transcription 3 GI:21618340, NP_644805.1 14 cyclindependent kinase 2 GI:30582481, AAP35467.1 15 family with sequencesimilarity 3, member A GI:57284179, CAI43239.1 16 (FAM3A)

Other substitutions, modifications, changes and omissions may be made inthe design, operating conditions and arrangement of the aspects andembodiments described herein without departing from the spirit of theinvention as expressed in the appended claims.

Additional advantages, features and modifications will readily occur tothose skilled in the art. Therefore, the invention in its broaderaspects is not limited to the specific details, and representativedevices, shown and described herein. Accordingly, various modificationsmay be made without departing from the spirit or scope of the generalinventive concept as defined by the appended claims and theirequivalents.

All of the references cited herein, including patents, patentapplications, and publications, are hereby incorporated in theirentireties by reference.

The scope of the claims below is not restricted to the particularembodiments described above. The examples are described for illustrativepurposes and are not intended to limit the methods and compositions ofthe present disclosure in any manner. Those of skill in the art willrecognize a variety of parameters that can be changed or modified toyield the same results.

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The invention claimed is:
 1. A method of providing a diagnosis andprognosis of a subject having, or suspected of having, chronicobstructive pulmonary disease (COPD), and of treating the subject,comprising: making a determination of five or more different proteins inTable 7, or peptides of five or more different proteins in Table 7, in abiological sample from a subject, said method optionally comprisingmaking a determination of one or more proteins in Tables 2, 4, 5 and/or6, or one or more peptides of one or more proteins in Tables 2, 4, 5and/or 6, and providing said diagnosis and prognosis of COPD based onthe abundance of the five or more different proteins in Table 7; andconsistent with the determination, providing a diagnosis of the subjectas either having COPD or not having COPD; wherein, when the subject isdiagnosed as having COPD, a prognosis of rapid or slow decline in lungfunction is provided and the subject is treated by administering one ormore therapeutics selected from immunosuppressants, corticosteroids, 02-adrenergic receptor agonists, anticholinergics, and oxygen; whereinsaid determination is conducted by measuring the amount of one or morepeptides that each comprise 7 to 50 amino acids from each of the five ormore different proteins in Table 7; and wherein said biological sampleis plasma prepared from blood where the plasma has been depleted of itsmost abundant protein.
 2. The method of claim 1, comprising making adetermination of eight or more different proteins or peptides fromdifferent proteins in Table
 7. 3. The method of claim 1, wherein thediagnosis and prognosis is rapid decline COPD with an average annualloss of FEV₁ of 1.6% or more per year.
 4. The method of claim 1, whereinthe diagnosis and prognosis is slow decline COPD with an average annualloss of FEV₁ of 0.8% or less per year.
 5. The method of claim 1, whereinsaid determination is conducted by measuring or observing the quantityor concentration of one or more nucleic acids expressed from a geneencoding one or more different proteins or peptides of proteins inTables 2, 4, 5 6 and/or
 7. 6. The method of claim 1, wherein saiddiagnosis and prognosis is: (a) a diagnosis and prognosis of rapiddecline in lung function relative to individuals not having lungdisease, said method further comprising making a determination of one ormore proteins in any of Tables 2, 4, and/or 6(b), or one or morepeptides of the proteins in any of Tables 2, 4, and/or 6(b) in saidsample; (b) a diagnosis and prognosis of slow decline in lung functionrelative to individuals not having lung disease, said method furthercomprising making a determination of one or more proteins in any ofTables 2, 4, and/or 6(c), or one or more peptides of the proteins in anyof Tables 2, 4, and/or 6(c) in said sample; or (c) a diagnosis andprognosis of rapid decline in lung function relative to individualshaving a slow decline in lung function, said method further comprisingmaking a determination of one or more proteins in any of Tables 2, 4, 5and/or 6(d), or one or more peptides of the proteins in any of Tables 2,4, 5 and/or 6(d) in said sample.
 7. The method of claim 1, furthercomprising making a determination of one or more additional proteins, orpeptide fragments thereof, selected from the group consisting of:proinsulin, plasminogen, fibrinogen alpha polypeptide, interleukin 6,coagulation factor II, interleukein 1 beta, signal transducer andactivator of transcription 3, cyclin dependent kinase 2, family withsequence similarity 3 member A (FAM3A), and peptide fragment of any ofthe foregoing.
 8. A composition comprising five or more nucleic acidmolecules comprising a nucleotide sequence encoding the proteins and/orpeptides of those proteins recited in Table 7, or a complementarynucleotide sequence thereof, wherein said composition does not comprisenucleic acids encoding all proteins recited in Table 7 or theircomplementary sequences.
 9. The composition of claim 8, wherein saidcomposition is in the form of an array having the five or more nucleicacids attached to spatially addressable locations.
 10. A method ofproviding a diagnosis and prognosis of a subject having or suspected ofhaving COPD and of treating and following the course of COPD progressionin a subject having COPD comprising: (a) making a first determination ata first time, of one or more peptide fragments of five proteinsidentified in Table 7 in a first sample from the subject; (b) consistentwith the determination, providing a diagnosis of the subject as eitherhaving COPD, or not having COPD; wherein, when the subject is diagnosedas having COPD, further providing a prognosis of rapid or slow declinein lung function; (c) making a second determination of at least the sameproteins or peptide fragments from a second sample obtained from thesubject at a second time; and (d) comparing the first determination tothe second determination to determine the progression or regression ofCOPD; wherein, when the subject is diagnosed as having COPD,administering to the subject at least one therapeutic agent selectedfrom the group consisting of immunosuppressants, corticosteroids,β2-adrenergic receptor agonists, anticholinergics, and/or oxygen;wherein said or one or more peptide fragments each comprise 7 to 50amino acids; and wherein said first and second biological samples areplasma prepared from blood where the plasma has been depleted of itsmost abundant protein.
 11. The method of claim 10, wherein at least onetherapeutic agent, selected from the group consisting ofimmunosuppressants, corticosteroids, β2-adrenergic receptor agonists,and anticholinergics, is administered to said subject.
 12. The method ofclaim 11, wherein said first sample was obtained from said subjectbefore said second sample, and wherein said therapeutic agent isadministered after said first sample was obtained from said subject, andbefore said second sample was obtained from said subject.
 13. The methodof claim 12, wherein said therapeutic agent is selected from the groupconsisting of: corticosteroids, β2 adrenergic receptor agonists, andanticholinergics.
 14. The method of claim 12, further comprisingchanging the treatment of a subject based upon said diagnosis andprognosis.
 15. The method of claim 1, wherein said determination isconducted with tryptic peptides of five or more proteins in Table
 7. 16.The method of claim 10, wherein said first determination is conductedwith tryptic peptides of five or more proteins in Table
 7. 17. Themethod of claim 12, wherein said first determination is conducted withtryptic peptides of five or more proteins in Table
 7. 18. A method ofproviding a diagnosis and prognosis of a subject having, or suspected ofhaving, chronic obstructive pulmonary disease (COPD), and of treatingthe subject, comprising: making a determination of five or moredifferent proteins in Table 7, or peptides of five or more differentproteins in Table 7, in a biological sample from a subject; said methodcomprising making a determination of one or more additional proteins inTables 2, 4, 5 and/or 6, or one or more peptides of one or more proteinsin Tables 2, 4, 5 and/or 6, and providing said diagnosis or prognosis ofCOPD based on the abundance of the five or more different proteins inTable 7; and consistent with the determination, providing a diagnosis ofthe subject as either having COPD, or not having COPD; wherein, when thesubject is diagnosed as having COPD, a prognosis of rapid or slowdecline in lung function is provided and the subject is treated byadministering one or more therapeutic agents selected fromimmunosuppressants, corticosteroids, β2 -adrenergic receptor agonists,anticholinergics, and oxygen; wherein said or one or more peptides eachcomprise 7 to 50 amino acids; and wherein said biological sample isplasma prepared from blood where the plasma has been depleted of itsmost abundant protein.
 19. A method of providing a diagnosis andprognosis of a subject having or suspected of having COPD and oftreating and following the course of COPD in a subject having COPDcomprising: (a) making a first determination, at a first time, of atleast five proteins or peptide fragments of five proteins identified inTable 7 in a first sample from the subject; (b) consistent with thedetermination, providing a diagnosis of the subject as either havingCOPD, or not having COPD; wherein, when the subject is diagnosed ashaving COPD, further providing a prognosis of rapid or slow decline inlung function; (c) making a second determination of at least the sameproteins or peptide fragments from a second sample obtained from thesubject at a second time; and (d) comparing the first determination tothe second determination to determine the progression or regression ofCOPD; wherein, when the subject is diagnosed as having COPD,administering to the subject at least one therapeutic agent selectedfrom the group consisting of immunosuppressants, corticosteroids,β2-adrenergic receptor agonists, anticholinergics, and/or oxygen;wherein said peptide fragments each comprise 7 to 50 amino acids; andwherein said first and second biological samples are plasma preparedfrom blood where the plasma has been depleted of its most abundantprotein.
 20. A composition comprising: a) an array having five or moreproteins identified in Table 7 or peptide fragments of five or moreproteins identified in Table 7 attached to five or more differentspatially addressable locations of the array; or b) an array having fiveor more antibodies or antigen binding fragments thereof that bindpeptides of five or more proteins in Table 7 attached to five or moredifferent spatially addressable locations of the array.
 21. Thecomposition of claim 20, wherein at least one of the proteins, peptides,antibodies or antigen binding fragments is covalently bound to saidarray.